Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
History is littered with hundreds of conflicts over the future of a community, group, location or business that were "resolved" when one of the parties stepped ahead and destroyed what was there. With the original point of contention destroyed, the debates would fall to the wayside. Archive Team believes that by duplicated condemned data, the conversation and debate can continue, as well as the richness and insight gained by keeping the materials. Our projects have ranged in size from a single volunteer downloading the data to a small-but-critical site, to over 100 volunteers stepping forward to acquire terabytes of user-created data to save for future generations.
The main site for Archive Team is at archiveteam.org and contains up to the date information on various projects, manifestos, plans and walkthroughs.
This collection contains the output of many Archive Team projects, both ongoing and completed. Thanks to the generous providing of disk space by the Internet Archive, multi-terabyte datasets can be made available, as well as in use by the Wayback Machine, providing a path back to lost websites and work.
Our collection has grown to the point of having sub-collections for the type of data we acquire. If you are seeking to browse the contents of these collections, the Wayback Machine is the best first stop. Otherwise, you are free to dig into the stacks to see what you may find.
The Archive Team Panic Downloads are full pulldowns of currently extant websites, meant to serve as emergency backups for needed sites that are in danger of closing, or which will be missed dearly if suddenly lost due to hard drive crashes or server failures.
Actions customers will now be able to clear stuck workflows by forcing a cancel request from the REST API. This is a new feature and the existing endpoint to cancel a workflow run will remain unchanged.
Sometimes an Actions workflow can become stuck in a state that will not respond to a cancel request. This could block other workflows from executing and would often require customers to contact GitHub Support to resolve the issue. Going forward, customers can invoke force-cancel from the REST API, which will bypass conditions that would otherwise cause the workflow execution to continue. Customers should still only use force-cancel if the workflow fails to respond to POST /repos/{owner}/{repo}/actions/runs/{run_id}/cancel.
The "GitHub EMU Connector" is maintained and supported by our partner, Ping Identity. Ping additionally maintains their own release notes for this connector.
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With CodeQL model packs for Java, users can improve their code scanning results by ensuring that any custom Java libraries and frameworks used by their codebase are recognised by CodeQL.
The out-of-the-box CodeQL threat models provide great coverage for identifying large numbers of potential vulnerabilities in GitHub repositories using code scanning. We are continually working to improve CodeQL's ability to recognize and track potential sources of untrusted data to potentially-vulnerable locations ('sinks'). To do that, we keep a close eye on the most widely-used open-source libraries and frameworks. That way, CodeQL can recognize untrusted data that enters an application through, for example, commonly-used web frameworks. We are even using advances in AI to boost our threat modeling efforts and help developers write even more secure code.
There will always be cases which are not covered by CodeQL's standard threat models, such as custom-built or inner-sourced frameworks and libraries. Using CodeQL's new model pack functionality for Java (beta), security teams and security-conscious developers can create custom models that help CodeQL detect and flag additional security vulnerabilities. These custom model packs work seamlessly in GitHub code scanning, which means developers get the most relevant code scanning alerts during their day-to-day work.
CodeQL model packs are part of the CodeQL package management ecosystem. The packs contain structured data which describe whether a method within a library is a taint source, sink, or propagator (also known as a flow summary). You can create CodeQL model packs for Java using the CodeQL model editor, a new feature in the CodeQL extension for VS Code. The CodeQL model editor includes support for:
identifying methods in your codebase that aren't recognised by the standard CodeQL analysis
interactively classifying those methods as a source, sink, or summary
automatically generating a CodeQL model pack that can be easily added to code scanning.
For more information about using CodeQL model packs in code scanning, see: