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  • Spring JMS MQJE001: Completion Code '2', Reason '2042'.

    - by john
    My setup is Spring 3 JMS, MVC + Websphere MQ + Websphere 7 <!-- this is the Message Driven POJO (MDP) --> <bean id="messageListener" class="com.SomeListener" /> <!-- and this is the message listener container --> <bean id="jmsContainer" class="org.springframework.jms.listener.DefaultMessageListenerContainer"> <property name="connectionFactory" ref="xxxCF" /> <property name="destination" ref="someQueue" /> <property name="messageListener" ref="messageListener" /> </bean> When I start up the server, the listener seems to start correctly since it receives the messages that are on the queue as I put them. However, once I run any simple controller/action that doesn't even have anything to do with JMS it gives me the message below over and over... DefaultMessag W org.springframework.jms.listener.DefaultMessageListenerContainer handleListenerSetupFailure Setup of JMS message listener invoker failed for destination 'queue:///ABCDEF.EFF.OUT?persistence=-1' - trying to recover. Cause: MQJMS2008: failed to open MQ queue ''.; nested exception is com.ibm.mq.MQException: MQJE001: Completion Code '2', Reason '2042'. DefaultMessag I org.springframework.jms.listener.DefaultMessageListenerContainer refreshConnectionUntilSuccessful Successfully refreshed JMS Connection ConnectionEve W J2CA0206W: A connection error occurred. To help determine the problem, enable the Diagnose Connection Usage option on the Connection Factory or Data Source. ConnectionEve A J2CA0056I: The Connection Manager received a fatal connection error from the Resource Adapter for resource JMS$XXXQCF$JMSManagedConnection@2. The exception is: javax.jms.JMSException: MQJMS2008: failed to open MQ queue ''. ConnectionEve W J2CA0206W: A connection error occurred. To help determine the problem, enable the Diagnose Connection Usage option on the Connection Factory or Data Source. ConnectionEve A J2CA0056I: The Connection Manager received a fatal connection error from the Resource Adapter for resource jms/XXXQCF. The exception is: javax.jms.JMSException: MQJMS2008: failed to open MQ queue ''. The original listener seems to be still running correctly...but I think the controller is somehow triggering off another connection? Does anyone know what I should check for or what might cause this issue? thanks

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  • CSS/JavaScript/hacking: Detect :visited styling on a link *without* checking it directly OR do it fa

    - by Sai Emrys
    This is for research purposes on http://cssfingerprint.com Consider the following code: <style> div.csshistory a { display: none; color: #00ff00;} div.csshistory a:visited { display: inline; color: #ff0000;} </style> <div id="batch" class="csshistory"> <a id="1" href="http://foo.com">anything you want here</a> <a id="2" href="http://bar.com">anything you want here</a> [etc * ~2000] </div> My goal is to detect whether foo has been rendered using the :visited styling. I want to detect whether foo.com is visited without directly looking at $('1').getComputedStyle (or in Internet Explorer, currentStyle), or any other direct method on that element. The purpose of this is to get around a potential browser restriction that would prevent direct inspection of the style of visited links. For instance, maybe you can put a sub-element in the <a> tag, or check the styling of the text directly; etc. Any method that does not directly or indierctly rely on $('1').anything is acceptable. Doing something clever with the child or parent is probably necessary. Note that for the purposes of this point only, the scenario is that the browser will lie to JavaScript about all properties of the <a> element (but not others), and that it will only render color: in :visited. Therefore, methods that rely on e.g. text size or background-image will not meet this requirement. I want to improve the speed of my current scraping methods. The majority of time (at least with the jQuery method in Firefox) is spent on document.body.appendChild(batch), so finding a way to improve that call would probably most effective. See http://cssfingerprint.com/about and http://cssfingerprint.com/results for current speed test results. The methods I am currently using can be seen at http://github.com/saizai/cssfingerprint/blob/master/public/javascripts/history_scrape.js To summarize for tl;dr, they are: set color or display on :visited per above, and check each one directly w/ getComputedStyle put the ID of the link (plus a space) inside the <a> tag, and using jQuery's :visible selector, extract only the visible text (= the visited link IDs) FWIW, I'm a white hat, and I'm doing this in consultation with the EFF and some other fairly well known security researchers. If you contribute a new method or speedup, you'll get thanked at http://cssfingerprint.com/about (if you want to be :-P), and potentially in a future published paper. ETA: The bounty will be rewarded only for suggestions that can, on Firefox, avoid the hypothetical restriction described in point 1 above, or perform at least 10% faster, on any browser for which I have sufficient current data, than my best performing methods listed in the graph at http://cssfingerprint.com/about In case more than one suggestion fits either criterion, the one that does best wins.

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  • Toorcon14

    - by danx
    Toorcon 2012 Information Security Conference San Diego, CA, http://www.toorcon.org/ Dan Anderson, October 2012 It's almost Halloween, and we all know what that means—yes, of course, it's time for another Toorcon Conference! Toorcon is an annual conference for people interested in computer security. This includes the whole range of hackers, computer hobbyists, professionals, security consultants, press, law enforcement, prosecutors, FBI, etc. We're at Toorcon 14—see earlier blogs for some of the previous Toorcon's I've attended (back to 2003). This year's "con" was held at the Westin on Broadway in downtown San Diego, California. The following are not necessarily my views—I'm just the messenger—although I could have misquoted or misparaphrased the speakers. Also, I only reviewed some of the talks, below, which I attended and interested me. MalAndroid—the Crux of Android Infections, Aditya K. Sood Programming Weird Machines with ELF Metadata, Rebecca "bx" Shapiro Privacy at the Handset: New FCC Rules?, Valkyrie Hacking Measured Boot and UEFI, Dan Griffin You Can't Buy Security: Building the Open Source InfoSec Program, Boris Sverdlik What Journalists Want: The Investigative Reporters' Perspective on Hacking, Dave Maas & Jason Leopold Accessibility and Security, Anna Shubina Stop Patching, for Stronger PCI Compliance, Adam Brand McAfee Secure & Trustmarks — a Hacker's Best Friend, Jay James & Shane MacDougall MalAndroid—the Crux of Android Infections Aditya K. Sood, IOActive, Michigan State PhD candidate Aditya talked about Android smartphone malware. There's a lot of old Android software out there—over 50% Gingerbread (2.3.x)—and most have unpatched vulnerabilities. Of 9 Android vulnerabilities, 8 have known exploits (such as the old Gingerbread Global Object Table exploit). Android protection includes sandboxing, security scanner, app permissions, and screened Android app market. The Android permission checker has fine-grain resource control, policy enforcement. Android static analysis also includes a static analysis app checker (bouncer), and a vulnerablity checker. What security problems does Android have? User-centric security, which depends on the user to grant permission and make smart decisions. But users don't care or think about malware (the're not aware, not paranoid). All they want is functionality, extensibility, mobility Android had no "proper" encryption before Android 3.0 No built-in protection against social engineering and web tricks Alternative Android app markets are unsafe. Simply visiting some markets can infect Android Aditya classified Android Malware types as: Type A—Apps. These interact with the Android app framework. For example, a fake Netflix app. Or Android Gold Dream (game), which uploads user files stealthy manner to a remote location. Type K—Kernel. Exploits underlying Linux libraries or kernel Type H—Hybrid. These use multiple layers (app framework, libraries, kernel). These are most commonly used by Android botnets, which are popular with Chinese botnet authors What are the threats from Android malware? These incude leak info (contacts), banking fraud, corporate network attacks, malware advertising, malware "Hackivism" (the promotion of social causes. For example, promiting specific leaders of the Tunisian or Iranian revolutions. Android malware is frequently "masquerated". That is, repackaged inside a legit app with malware. To avoid detection, the hidden malware is not unwrapped until runtime. The malware payload can be hidden in, for example, PNG files. Less common are Android bootkits—there's not many around. What they do is hijack the Android init framework—alteering system programs and daemons, then deletes itself. For example, the DKF Bootkit (China). Android App Problems: no code signing! all self-signed native code execution permission sandbox — all or none alternate market places no robust Android malware detection at network level delayed patch process Programming Weird Machines with ELF Metadata Rebecca "bx" Shapiro, Dartmouth College, NH https://github.com/bx/elf-bf-tools @bxsays on twitter Definitions. "ELF" is an executable file format used in linking and loading executables (on UNIX/Linux-class machines). "Weird machine" uses undocumented computation sources (I think of them as unintended virtual machines). Some examples of "weird machines" are those that: return to weird location, does SQL injection, corrupts the heap. Bx then talked about using ELF metadata as (an uintended) "weird machine". Some ELF background: A compiler takes source code and generates a ELF object file (hello.o). A static linker makes an ELF executable from the object file. A runtime linker and loader takes ELF executable and loads and relocates it in memory. The ELF file has symbols to relocate functions and variables. ELF has two relocation tables—one at link time and another one at loading time: .rela.dyn (link time) and .dynsym (dynamic table). GOT: Global Offset Table of addresses for dynamically-linked functions. PLT: Procedure Linkage Tables—works with GOT. The memory layout of a process (not the ELF file) is, in order: program (+ heap), dynamic libraries, libc, ld.so, stack (which includes the dynamic table loaded into memory) For ELF, the "weird machine" is found and exploited in the loader. ELF can be crafted for executing viruses, by tricking runtime into executing interpreted "code" in the ELF symbol table. One can inject parasitic "code" without modifying the actual ELF code portions. Think of the ELF symbol table as an "assembly language" interpreter. It has these elements: instructions: Add, move, jump if not 0 (jnz) Think of symbol table entries as "registers" symbol table value is "contents" immediate values are constants direct values are addresses (e.g., 0xdeadbeef) move instruction: is a relocation table entry add instruction: relocation table "addend" entry jnz instruction: takes multiple relocation table entries The ELF weird machine exploits the loader by relocating relocation table entries. The loader will go on forever until told to stop. It stores state on stack at "end" and uses IFUNC table entries (containing function pointer address). The ELF weird machine, called "Brainfu*k" (BF) has: 8 instructions: pointer inc, dec, inc indirect, dec indirect, jump forward, jump backward, print. Three registers - 3 registers Bx showed example BF source code that implemented a Turing machine printing "hello, world". More interesting was the next demo, where bx modified ping. Ping runs suid as root, but quickly drops privilege. BF modified the loader to disable the library function call dropping privilege, so it remained as root. Then BF modified the ping -t argument to execute the -t filename as root. It's best to show what this modified ping does with an example: $ whoami bx $ ping localhost -t backdoor.sh # executes backdoor $ whoami root $ The modified code increased from 285948 bytes to 290209 bytes. A BF tool compiles "executable" by modifying the symbol table in an existing ELF executable. The tool modifies .dynsym and .rela.dyn table, but not code or data. Privacy at the Handset: New FCC Rules? "Valkyrie" (Christie Dudley, Santa Clara Law JD candidate) Valkyrie talked about mobile handset privacy. Some background: Senator Franken (also a comedian) became alarmed about CarrierIQ, where the carriers track their customers. Franken asked the FCC to find out what obligations carriers think they have to protect privacy. The carriers' response was that they are doing just fine with self-regulation—no worries! Carriers need to collect data, such as missed calls, to maintain network quality. But carriers also sell data for marketing. Verizon sells customer data and enables this with a narrow privacy policy (only 1 month to opt out, with difficulties). The data sold is not individually identifiable and is aggregated. But Verizon recommends, as an aggregation workaround to "recollate" data to other databases to identify customers indirectly. The FCC has regulated telephone privacy since 1934 and mobile network privacy since 2007. Also, the carriers say mobile phone privacy is a FTC responsibility (not FCC). FTC is trying to improve mobile app privacy, but FTC has no authority over carrier / customer relationships. As a side note, Apple iPhones are unique as carriers have extra control over iPhones they don't have with other smartphones. As a result iPhones may be more regulated. Who are the consumer advocates? Everyone knows EFF, but EPIC (Electrnic Privacy Info Center), although more obsecure, is more relevant. What to do? Carriers must be accountable. Opt-in and opt-out at any time. Carriers need incentive to grant users control for those who want it, by holding them liable and responsible for breeches on their clock. Location information should be added current CPNI privacy protection, and require "Pen/trap" judicial order to obtain (and would still be a lower standard than 4th Amendment). Politics are on a pro-privacy swing now, with many senators and the Whitehouse. There will probably be new regulation soon, and enforcement will be a problem, but consumers will still have some benefit. Hacking Measured Boot and UEFI Dan Griffin, JWSecure, Inc., Seattle, @JWSdan Dan talked about hacking measured UEFI boot. First some terms: UEFI is a boot technology that is replacing BIOS (has whitelisting and blacklisting). UEFI protects devices against rootkits. TPM - hardware security device to store hashs and hardware-protected keys "secure boot" can control at firmware level what boot images can boot "measured boot" OS feature that tracks hashes (from BIOS, boot loader, krnel, early drivers). "remote attestation" allows remote validation and control based on policy on a remote attestation server. Microsoft pushing TPM (Windows 8 required), but Google is not. Intel TianoCore is the only open source for UEFI. Dan has Measured Boot Tool at http://mbt.codeplex.com/ with a demo where you can also view TPM data. TPM support already on enterprise-class machines. UEFI Weaknesses. UEFI toolkits are evolving rapidly, but UEFI has weaknesses: assume user is an ally trust TPM implicitly, and attached to computer hibernate file is unprotected (disk encryption protects against this) protection migrating from hardware to firmware delays in patching and whitelist updates will UEFI really be adopted by the mainstream (smartphone hardware support, bank support, apathetic consumer support) You Can't Buy Security: Building the Open Source InfoSec Program Boris Sverdlik, ISDPodcast.com co-host Boris talked about problems typical with current security audits. "IT Security" is an oxymoron—IT exists to enable buiness, uptime, utilization, reporting, but don't care about security—IT has conflict of interest. There's no Magic Bullet ("blinky box"), no one-size-fits-all solution (e.g., Intrusion Detection Systems (IDSs)). Regulations don't make you secure. The cloud is not secure (because of shared data and admin access). Defense and pen testing is not sexy. Auditors are not solution (security not a checklist)—what's needed is experience and adaptability—need soft skills. Step 1: First thing is to Google and learn the company end-to-end before you start. Get to know the management team (not IT team), meet as many people as you can. Don't use arbitrary values such as CISSP scores. Quantitive risk assessment is a myth (e.g. AV*EF-SLE). Learn different Business Units, legal/regulatory obligations, learn the business and where the money is made, verify company is protected from script kiddies (easy), learn sensitive information (IP, internal use only), and start with low-hanging fruit (customer service reps and social engineering). Step 2: Policies. Keep policies short and relevant. Generic SANS "security" boilerplate policies don't make sense and are not followed. Focus on acceptable use, data usage, communications, physical security. Step 3: Implementation: keep it simple stupid. Open source, although useful, is not free (implementation cost). Access controls with authentication & authorization for local and remote access. MS Windows has it, otherwise use OpenLDAP, OpenIAM, etc. Application security Everyone tries to reinvent the wheel—use existing static analysis tools. Review high-risk apps and major revisions. Don't run different risk level apps on same system. Assume host/client compromised and use app-level security control. Network security VLAN != segregated because there's too many workarounds. Use explicit firwall rules, active and passive network monitoring (snort is free), disallow end user access to production environment, have a proxy instead of direct Internet access. Also, SSL certificates are not good two-factor auth and SSL does not mean "safe." Operational Controls Have change, patch, asset, & vulnerability management (OSSI is free). For change management, always review code before pushing to production For logging, have centralized security logging for business-critical systems, separate security logging from administrative/IT logging, and lock down log (as it has everything). Monitor with OSSIM (open source). Use intrusion detection, but not just to fulfill a checkbox: build rules from a whitelist perspective (snort). OSSEC has 95% of what you need. Vulnerability management is a QA function when done right: OpenVas and Seccubus are free. Security awareness The reality is users will always click everything. Build real awareness, not compliance driven checkbox, and have it integrated into the culture. Pen test by crowd sourcing—test with logging COSSP http://www.cossp.org/ - Comprehensive Open Source Security Project What Journalists Want: The Investigative Reporters' Perspective on Hacking Dave Maas, San Diego CityBeat Jason Leopold, Truthout.org The difference between hackers and investigative journalists: For hackers, the motivation varies, but method is same, technological specialties. For investigative journalists, it's about one thing—The Story, and they need broad info-gathering skills. J-School in 60 Seconds: Generic formula: Person or issue of pubic interest, new info, or angle. Generic criteria: proximity, prominence, timeliness, human interest, oddity, or consequence. Media awareness of hackers and trends: journalists becoming extremely aware of hackers with congressional debates (privacy, data breaches), demand for data-mining Journalists, use of coding and web development for Journalists, and Journalists busted for hacking (Murdock). Info gathering by investigative journalists include Public records laws. Federal Freedom of Information Act (FOIA) is good, but slow. California Public Records Act is a lot stronger. FOIA takes forever because of foot-dragging—it helps to be specific. Often need to sue (especially FBI). CPRA is faster, and requests can be vague. Dumps and leaks (a la Wikileaks) Journalists want: leads, protecting ourselves, our sources, and adapting tools for news gathering (Google hacking). Anonomity is important to whistleblowers. They want no digital footprint left behind (e.g., email, web log). They don't trust encryption, want to feel safe and secure. Whistleblower laws are very weak—there's no upside for whistleblowers—they have to be very passionate to do it. Accessibility and Security or: How I Learned to Stop Worrying and Love the Halting Problem Anna Shubina, Dartmouth College Anna talked about how accessibility and security are related. Accessibility of digital content (not real world accessibility). mostly refers to blind users and screenreaders, for our purpose. Accessibility is about parsing documents, as are many security issues. "Rich" executable content causes accessibility to fail, and often causes security to fail. For example MS Word has executable format—it's not a document exchange format—more dangerous than PDF or HTML. Accessibility is often the first and maybe only sanity check with parsing. They have no choice because someone may want to read what you write. Google, for example, is very particular about web browser you use and are bad at supporting other browsers. Uses JavaScript instead of links, often requiring mouseover to display content. PDF is a security nightmare. Executible format, embedded flash, JavaScript, etc. 15 million lines of code. Google Chrome doesn't handle PDF correctly, causing several security bugs. PDF has an accessibility checker and PDF tagging, to help with accessibility. But no PDF checker checks for incorrect tags, untagged content, or validates lists or tables. None check executable content at all. The "Halting Problem" is: can one decide whether a program will ever stop? The answer, in general, is no (Rice's theorem). The same holds true for accessibility checkers. Language-theoretic Security says complicated data formats are hard to parse and cannot be solved due to the Halting Problem. W3C Web Accessibility Guidelines: "Perceivable, Operable, Understandable, Robust" Not much help though, except for "Robust", but here's some gems: * all information should be parsable (paraphrasing) * if not parsable, cannot be converted to alternate formats * maximize compatibility in new document formats Executible webpages are bad for security and accessibility. They say it's for a better web experience. But is it necessary to stuff web pages with JavaScript for a better experience? A good example is The Drudge Report—it has hand-written HTML with no JavaScript, yet drives a lot of web traffic due to good content. A bad example is Google News—hidden scrollbars, guessing user input. Solutions: Accessibility and security problems come from same source Expose "better user experience" myth Keep your corner of Internet parsable Remember "Halting Problem"—recognize false solutions (checking and verifying tools) Stop Patching, for Stronger PCI Compliance Adam Brand, protiviti @adamrbrand, http://www.picfun.com/ Adam talked about PCI compliance for retail sales. Take an example: for PCI compliance, 50% of Brian's time (a IT guy), 960 hours/year was spent patching POSs in 850 restaurants. Often applying some patches make no sense (like fixing a browser vulnerability on a server). "Scanner worship" is overuse of vulnerability scanners—it gives a warm and fuzzy and it's simple (red or green results—fix reds). Scanners give a false sense of security. In reality, breeches from missing patches are uncommon—more common problems are: default passwords, cleartext authentication, misconfiguration (firewall ports open). Patching Myths: Myth 1: install within 30 days of patch release (but PCI §6.1 allows a "risk-based approach" instead). Myth 2: vendor decides what's critical (also PCI §6.1). But §6.2 requires user ranking of vulnerabilities instead. Myth 3: scan and rescan until it passes. But PCI §11.2.1b says this applies only to high-risk vulnerabilities. Adam says good recommendations come from NIST 800-40. Instead use sane patching and focus on what's really important. From NIST 800-40: Proactive: Use a proactive vulnerability management process: use change control, configuration management, monitor file integrity. Monitor: start with NVD and other vulnerability alerts, not scanner results. Evaluate: public-facing system? workstation? internal server? (risk rank) Decide:on action and timeline Test: pre-test patches (stability, functionality, rollback) for change control Install: notify, change control, tickets McAfee Secure & Trustmarks — a Hacker's Best Friend Jay James, Shane MacDougall, Tactical Intelligence Inc., Canada "McAfee Secure Trustmark" is a website seal marketed by McAfee. A website gets this badge if they pass their remote scanning. The problem is a removal of trustmarks act as flags that you're vulnerable. Easy to view status change by viewing McAfee list on website or on Google. "Secure TrustGuard" is similar to McAfee. Jay and Shane wrote Perl scripts to gather sites from McAfee and search engines. If their certification image changes to a 1x1 pixel image, then they are longer certified. Their scripts take deltas of scans to see what changed daily. The bottom line is change in TrustGuard status is a flag for hackers to attack your site. Entire idea of seals is silly—you're raising a flag saying if you're vulnerable.

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  • Understanding G1 GC Logs

    - by poonam
    The purpose of this post is to explain the meaning of GC logs generated with some tracing and diagnostic options for G1 GC. We will take a look at the output generated with PrintGCDetails which is a product flag and provides the most detailed level of information. Along with that, we will also look at the output of two diagnostic flags that get enabled with -XX:+UnlockDiagnosticVMOptions option - G1PrintRegionLivenessInfo that prints the occupancy and the amount of space used by live objects in each region at the end of the marking cycle and G1PrintHeapRegions that provides detailed information on the heap regions being allocated and reclaimed. We will be looking at the logs generated with JDK 1.7.0_04 using these options. Option -XX:+PrintGCDetails Here's a sample log of G1 collection generated with PrintGCDetails. 0.522: [GC pause (young), 0.15877971 secs] [Parallel Time: 157.1 ms] [GC Worker Start (ms): 522.1 522.2 522.2 522.2 Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] [Processed Buffers : 2 2 3 2 Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] [GC Worker Other (ms): 0.3 0.3 0.3 0.3 Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] [Clear CT: 0.1 ms] [Other: 1.5 ms] [Choose CSet: 0.0 ms] [Ref Proc: 0.3 ms] [Ref Enq: 0.0 ms] [Free CSet: 0.3 ms] [Eden: 12M(12M)->0B(10M) Survivors: 0B->2048K Heap: 13M(64M)->9739K(64M)] [Times: user=0.59 sys=0.02, real=0.16 secs] This is the typical log of an Evacuation Pause (G1 collection) in which live objects are copied from one set of regions (young OR young+old) to another set. It is a stop-the-world activity and all the application threads are stopped at a safepoint during this time. This pause is made up of several sub-tasks indicated by the indentation in the log entries. Here's is the top most line that gets printed for the Evacuation Pause. 0.522: [GC pause (young), 0.15877971 secs] This is the highest level information telling us that it is an Evacuation Pause that started at 0.522 secs from the start of the process, in which all the regions being evacuated are Young i.e. Eden and Survivor regions. This collection took 0.15877971 secs to finish. Evacuation Pauses can be mixed as well. In which case the set of regions selected include all of the young regions as well as some old regions. 1.730: [GC pause (mixed), 0.32714353 secs] Let's take a look at all the sub-tasks performed in this Evacuation Pause. [Parallel Time: 157.1 ms] Parallel Time is the total elapsed time spent by all the parallel GC worker threads. The following lines correspond to the parallel tasks performed by these worker threads in this total parallel time, which in this case is 157.1 ms. [GC Worker Start (ms): 522.1 522.2 522.2 522.2Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] The first line tells us the start time of each of the worker thread in milliseconds. The start times are ordered with respect to the worker thread ids – thread 0 started at 522.1ms and thread 1 started at 522.2ms from the start of the process. The second line tells the Avg, Min, Max and Diff of the start times of all of the worker threads. [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] This gives us the time spent by each worker thread scanning the roots (globals, registers, thread stacks and VM data structures). Here, thread 0 took 1.6ms to perform the root scanning task and thread 1 took 1.5 ms. The second line clearly shows the Avg, Min, Max and Diff of the times spent by all the worker threads. [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] Update RS gives us the time each thread spent in updating the Remembered Sets. Remembered Sets are the data structures that keep track of the references that point into a heap region. Mutator threads keep changing the object graph and thus the references that point into a particular region. We keep track of these changes in buffers called Update Buffers. The Update RS sub-task processes the update buffers that were not able to be processed concurrently, and updates the corresponding remembered sets of all regions. [Processed Buffers : 2 2 3 2Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] This tells us the number of Update Buffers (mentioned above) processed by each worker thread. [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] These are the times each worker thread had spent in scanning the Remembered Sets. Remembered Set of a region contains cards that correspond to the references pointing into that region. This phase scans those cards looking for the references pointing into all the regions of the collection set. [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] These are the times spent by each worker thread copying live objects from the regions in the Collection Set to the other regions. [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] Termination time is the time spent by the worker thread offering to terminate. But before terminating, it checks the work queues of other threads and if there are still object references in other work queues, it tries to steal object references, and if it succeeds in stealing a reference, it processes that and offers to terminate again. [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] This gives the number of times each thread has offered to terminate. [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] These are the times in milliseconds at which each worker thread stopped. [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] These are the total lifetimes of each worker thread. [GC Worker Other (ms): 0.3 0.3 0.3 0.3Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] These are the times that each worker thread spent in performing some other tasks that we have not accounted above for the total Parallel Time. [Clear CT: 0.1 ms] This is the time spent in clearing the Card Table. This task is performed in serial mode. [Other: 1.5 ms] Time spent in the some other tasks listed below. The following sub-tasks (which individually may be parallelized) are performed serially. [Choose CSet: 0.0 ms] Time spent in selecting the regions for the Collection Set. [Ref Proc: 0.3 ms] Total time spent in processing Reference objects. [Ref Enq: 0.0 ms] Time spent in enqueuing references to the ReferenceQueues. [Free CSet: 0.3 ms] Time spent in freeing the collection set data structure. [Eden: 12M(12M)->0B(13M) Survivors: 0B->2048K Heap: 14M(64M)->9739K(64M)] This line gives the details on the heap size changes with the Evacuation Pause. This shows that Eden had the occupancy of 12M and its capacity was also 12M before the collection. After the collection, its occupancy got reduced to 0 since everything is evacuated/promoted from Eden during a collection, and its target size grew to 13M. The new Eden capacity of 13M is not reserved at this point. This value is the target size of the Eden. Regions are added to Eden as the demand is made and when the added regions reach to the target size, we start the next collection. Similarly, Survivors had the occupancy of 0 bytes and it grew to 2048K after the collection. The total heap occupancy and capacity was 14M and 64M receptively before the collection and it became 9739K and 64M after the collection. Apart from the evacuation pauses, G1 also performs concurrent-marking to build the live data information of regions. 1.416: [GC pause (young) (initial-mark), 0.62417980 secs] ….... 2.042: [GC concurrent-root-region-scan-start] 2.067: [GC concurrent-root-region-scan-end, 0.0251507] 2.068: [GC concurrent-mark-start] 3.198: [GC concurrent-mark-reset-for-overflow] 4.053: [GC concurrent-mark-end, 1.9849672 sec] 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.090: [GC concurrent-cleanup-start] 4.091: [GC concurrent-cleanup-end, 0.0002721] The first phase of a marking cycle is Initial Marking where all the objects directly reachable from the roots are marked and this phase is piggy-backed on a fully young Evacuation Pause. 2.042: [GC concurrent-root-region-scan-start] This marks the start of a concurrent phase that scans the set of root-regions which are directly reachable from the survivors of the initial marking phase. 2.067: [GC concurrent-root-region-scan-end, 0.0251507] End of the concurrent root region scan phase and it lasted for 0.0251507 seconds. 2.068: [GC concurrent-mark-start] Start of the concurrent marking at 2.068 secs from the start of the process. 3.198: [GC concurrent-mark-reset-for-overflow] This indicates that the global marking stack had became full and there was an overflow of the stack. Concurrent marking detected this overflow and had to reset the data structures to start the marking again. 4.053: [GC concurrent-mark-end, 1.9849672 sec] End of the concurrent marking phase and it lasted for 1.9849672 seconds. 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] This corresponds to the remark phase which is a stop-the-world phase. It completes the left over marking work (SATB buffers processing) from the previous phase. In this case, this phase took 0.0030184 secs and out of which 0.0000254 secs were spent on Reference processing. 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] Cleanup phase which is again a stop-the-world phase. It goes through the marking information of all the regions, computes the live data information of each region, resets the marking data structures and sorts the regions according to their gc-efficiency. In this example, the total heap size is 138M and after the live data counting it was found that the total live data size dropped down from 117M to 106M. 4.090: [GC concurrent-cleanup-start] This concurrent cleanup phase frees up the regions that were found to be empty (didn't contain any live data) during the previous stop-the-world phase. 4.091: [GC concurrent-cleanup-end, 0.0002721] Concurrent cleanup phase took 0.0002721 secs to free up the empty regions. Option -XX:G1PrintRegionLivenessInfo Now, let's look at the output generated with the flag G1PrintRegionLivenessInfo. This is a diagnostic option and gets enabled with -XX:+UnlockDiagnosticVMOptions. G1PrintRegionLivenessInfo prints the live data information of each region during the Cleanup phase of the concurrent-marking cycle. 26.896: [GC cleanup ### PHASE Post-Marking @ 26.896### HEAP committed: 0x02e00000-0x0fe00000 reserved: 0x02e00000-0x12e00000 region-size: 1048576 Cleanup phase of the concurrent-marking cycle started at 26.896 secs from the start of the process and this live data information is being printed after the marking phase. Committed G1 heap ranges from 0x02e00000 to 0x0fe00000 and the total G1 heap reserved by JVM is from 0x02e00000 to 0x12e00000. Each region in the G1 heap is of size 1048576 bytes. ### type address-range used prev-live next-live gc-eff### (bytes) (bytes) (bytes) (bytes/ms) This is the header of the output that tells us about the type of the region, address-range of the region, used space in the region, live bytes in the region with respect to the previous marking cycle, live bytes in the region with respect to the current marking cycle and the GC efficiency of that region. ### FREE 0x02e00000-0x02f00000 0 0 0 0.0 This is a Free region. ### OLD 0x02f00000-0x03000000 1048576 1038592 1038592 0.0 Old region with address-range from 0x02f00000 to 0x03000000. Total used space in the region is 1048576 bytes, live bytes as per the previous marking cycle are 1038592 and live bytes with respect to the current marking cycle are also 1038592. The GC efficiency has been computed as 0. ### EDEN 0x03400000-0x03500000 20992 20992 20992 0.0 This is an Eden region. ### HUMS 0x0ae00000-0x0af00000 1048576 1048576 1048576 0.0### HUMC 0x0af00000-0x0b000000 1048576 1048576 1048576 0.0### HUMC 0x0b000000-0x0b100000 1048576 1048576 1048576 0.0### HUMC 0x0b100000-0x0b200000 1048576 1048576 1048576 0.0### HUMC 0x0b200000-0x0b300000 1048576 1048576 1048576 0.0### HUMC 0x0b300000-0x0b400000 1048576 1048576 1048576 0.0### HUMC 0x0b400000-0x0b500000 1001480 1001480 1001480 0.0 These are the continuous set of regions called Humongous regions for storing a large object. HUMS (Humongous starts) marks the start of the set of humongous regions and HUMC (Humongous continues) tags the subsequent regions of the humongous regions set. ### SURV 0x09300000-0x09400000 16384 16384 16384 0.0 This is a Survivor region. ### SUMMARY capacity: 208.00 MB used: 150.16 MB / 72.19 % prev-live: 149.78 MB / 72.01 % next-live: 142.82 MB / 68.66 % At the end, a summary is printed listing the capacity, the used space and the change in the liveness after the completion of concurrent marking. In this case, G1 heap capacity is 208MB, total used space is 150.16MB which is 72.19% of the total heap size, live data in the previous marking was 149.78MB which was 72.01% of the total heap size and the live data as per the current marking is 142.82MB which is 68.66% of the total heap size. Option -XX:+G1PrintHeapRegions G1PrintHeapRegions option logs the regions related events when regions are committed, allocated into or are reclaimed. COMMIT/UNCOMMIT events G1HR COMMIT [0x6e900000,0x6ea00000]G1HR COMMIT [0x6ea00000,0x6eb00000] Here, the heap is being initialized or expanded and the region (with bottom: 0x6eb00000 and end: 0x6ec00000) is being freshly committed. COMMIT events are always generated in order i.e. the next COMMIT event will always be for the uncommitted region with the lowest address. G1HR UNCOMMIT [0x72700000,0x72800000]G1HR UNCOMMIT [0x72600000,0x72700000] Opposite to COMMIT. The heap got shrunk at the end of a Full GC and the regions are being uncommitted. Like COMMIT, UNCOMMIT events are also generated in order i.e. the next UNCOMMIT event will always be for the committed region with the highest address. GC Cycle events G1HR #StartGC 7G1HR CSET 0x6e900000G1HR REUSE 0x70500000G1HR ALLOC(Old) 0x6f800000G1HR RETIRE 0x6f800000 0x6f821b20G1HR #EndGC 7 This shows start and end of an Evacuation pause. This event is followed by a GC counter tracking both evacuation pauses and Full GCs. Here, this is the 7th GC since the start of the process. G1HR #StartFullGC 17G1HR UNCOMMIT [0x6ed00000,0x6ee00000]G1HR POST-COMPACTION(Old) 0x6e800000 0x6e854f58G1HR #EndFullGC 17 Shows start and end of a Full GC. This event is also followed by the same GC counter as above. This is the 17th GC since the start of the process. ALLOC events G1HR ALLOC(Eden) 0x6e800000 The region with bottom 0x6e800000 just started being used for allocation. In this case it is an Eden region and allocated into by a mutator thread. G1HR ALLOC(StartsH) 0x6ec00000 0x6ed00000G1HR ALLOC(ContinuesH) 0x6ed00000 0x6e000000 Regions being used for the allocation of Humongous object. The object spans over two regions. G1HR ALLOC(SingleH) 0x6f900000 0x6f9eb010 Single region being used for the allocation of Humongous object. G1HR COMMIT [0x6ee00000,0x6ef00000]G1HR COMMIT [0x6ef00000,0x6f000000]G1HR COMMIT [0x6f000000,0x6f100000]G1HR COMMIT [0x6f100000,0x6f200000]G1HR ALLOC(StartsH) 0x6ee00000 0x6ef00000G1HR ALLOC(ContinuesH) 0x6ef00000 0x6f000000G1HR ALLOC(ContinuesH) 0x6f000000 0x6f100000G1HR ALLOC(ContinuesH) 0x6f100000 0x6f102010 Here, Humongous object allocation request could not be satisfied by the free committed regions that existed in the heap, so the heap needed to be expanded. Thus new regions are committed and then allocated into for the Humongous object. G1HR ALLOC(Old) 0x6f800000 Old region started being used for allocation during GC. G1HR ALLOC(Survivor) 0x6fa00000 Region being used for copying old objects into during a GC. Note that Eden and Humongous ALLOC events are generated outside the GC boundaries and Old and Survivor ALLOC events are generated inside the GC boundaries. Other Events G1HR RETIRE 0x6e800000 0x6e87bd98 Retire and stop using the region having bottom 0x6e800000 and top 0x6e87bd98 for allocation. Note that most regions are full when they are retired and we omit those events to reduce the output volume. A region is retired when another region of the same type is allocated or we reach the start or end of a GC(depending on the region). So for Eden regions: For example: 1. ALLOC(Eden) Foo2. ALLOC(Eden) Bar3. StartGC At point 2, Foo has just been retired and it was full. At point 3, Bar was retired and it was full. If they were not full when they were retired, we will have a RETIRE event: 1. ALLOC(Eden) Foo2. RETIRE Foo top3. ALLOC(Eden) Bar4. StartGC G1HR CSET 0x6e900000 Region (bottom: 0x6e900000) is selected for the Collection Set. The region might have been selected for the collection set earlier (i.e. when it was allocated). However, we generate the CSET events for all regions in the CSet at the start of a GC to make sure there's no confusion about which regions are part of the CSet. G1HR POST-COMPACTION(Old) 0x6e800000 0x6e839858 POST-COMPACTION event is generated for each non-empty region in the heap after a full compaction. A full compaction moves objects around, so we don't know what the resulting shape of the heap is (which regions were written to, which were emptied, etc.). To deal with this, we generate a POST-COMPACTION event for each non-empty region with its type (old/humongous) and the heap boundaries. At this point we should only have Old and Humongous regions, as we have collapsed the young generation, so we should not have eden and survivors. POST-COMPACTION events are generated within the Full GC boundary. G1HR CLEANUP 0x6f400000G1HR CLEANUP 0x6f300000G1HR CLEANUP 0x6f200000 These regions were found empty after remark phase of Concurrent Marking and are reclaimed shortly afterwards. G1HR #StartGC 5G1HR CSET 0x6f400000G1HR CSET 0x6e900000G1HR REUSE 0x6f800000 At the end of a GC we retire the old region we are allocating into. Given that its not full, we will carry on allocating into it during the next GC. This is what REUSE means. In the above case 0x6f800000 should have been the last region with an ALLOC(Old) event during the previous GC and should have been retired before the end of the previous GC. G1HR ALLOC-FORCE(Eden) 0x6f800000 A specialization of ALLOC which indicates that we have reached the max desired number of the particular region type (in this case: Eden), but we decided to allocate one more. Currently it's only used for Eden regions when we extend the young generation because we cannot do a GC as the GC-Locker is active. G1HR EVAC-FAILURE 0x6f800000 During a GC, we have failed to evacuate an object from the given region as the heap is full and there is no space left to copy the object. This event is generated within GC boundaries and exactly once for each region from which we failed to evacuate objects. When Heap Regions are reclaimed ? It is also worth mentioning when the heap regions in the G1 heap are reclaimed. All regions that are in the CSet (the ones that appear in CSET events) are reclaimed at the end of a GC. The exception to that are regions with EVAC-FAILURE events. All regions with CLEANUP events are reclaimed. After a Full GC some regions get reclaimed (the ones from which we moved the objects out). But that is not shown explicitly, instead the non-empty regions that are left in the heap are printed out with the POST-COMPACTION events.

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