Releasesby IbisAudit GitHub Code Quality finding dismissals and reopenings
GAyesterdayUnverifiedAdded Oct 14, 2026
You can now review manual dismissals and reopenings of GitHub Code Quality findings in your organization or enterprise audit log. Findings may appear in either your repository’s default-branch backlog or pull requests. Two new events record these actions: repo.code_quality_findings_dismissed records a dismissal of one or more backlog findings.
Topics: Observability, Developer tools
More GitHub Advanced Security releases
Every GitHub Advanced Security releaseSecret scanning blocks Anthropic keys by default, adds Salesforce
Secret scanning now detects new secret types from Salesforce, Anthropic, and Cloudsmith, with the new Anthropic secret types blocked with push protection by default. New secret scanning partner Salesforce is now a secret scanning partner.
Improved detection for withdrawn Dependabot alerts
You can now more easily detect withdrawn Dependabot alerts. Dependabot withdraws and removes an alert when the advisory or vulnerability that produced it is no longer valid. Two changes help you detect these withdrawals: Webhooks: The dependabot_alert webhook event now includes a withdrawn action.
Code scanning AI Scan metrics in security overview
Organization and enterprise administrators can now observe the impact of AI Scan for pull requests in security overview. New metrics show how many AI Scan findings were generated, resolved, the remediation rate, which repositories generated findings, trends over the selected reporting period, and how often developers applied autofix suggestions.
Push attribution for commits in limited public preview
GitHub now durably records the authenticated user who pushed each commit and surfaces that pusher identity in the UI and API alongside the existing author and committer fields. Commit author and committer fields are just strings that the pushing client supplies, so anyone with write access to a repository can set them to any name and email they choose.
Anonymous organization-level registries for Dependabot
You can now select Anonymous as the authentication method for an organization-level private registry. Use it for registries that Dependabot can reach without credentials, such as an internal package mirror that allows anonymous reads. On github.com, Dependabot update jobs can only reach hosts on the egress allowlist and the private registries you configure.
CodeQL 2.27.2 improves C++, Go, Rust, and JavaScript analysis
CodeQL 2.27.2 is now available, adding a C++ regular-expression parser and analysis improvements across several languages. CodeQL is the static analysis engine behind GitHub code scanning, which helps you find and remediate security issues in your code. The Default suite runs 498 security queries covering 170 CWEs.
Code scanning AI Scan enablement status in security overview
Organization and enterprise administrators can now see AI Scan for pull requests enablement status in the security overview coverage view. The code scanning summary shows enabled and not enabled repository counts, while repository rows show each repository’s effective AI Scan enablement.
Secret scanning adds detectors for Lovable, Supabase, and more
Secret scanning now detects new secret types from Lovable Labs, Pydantic Services Inc., and Supabase. New secret scanning partner The following provider joined the secret scanning partnership program.
Also shipped on Oct 13, 2026
GitHub in October 2026What's included:
- Three training methods: Supervised fine-tuning (SFT) , direct preference optimization (DPO) , and reinforcement learning with group relative policy optimization (GRPO) . Each method trains a low-rank adapter (LoRA) or the full model weights. Custom loss functions : Train with any objective you compute in PyTorch from the model's log-probabilities.
The AI.AGG function is generally available (GA)
The AI.AGG function is generally available (GA). You can use this function to semantically aggregate unstructured input data based on natural language instructions.
BigQuery generative AI functions now support the gemini-4-argon model
BigQuery generative AI functions now support the gemini-4-argon model. This model is generally available .
Gemini 4 Argon in CodeMender (Preview)
CodeMender now supports Gemini 4 Argon. To use it, pass --model gemini-4-argon to cm find , cm verify , or cm fix . Gemini 3.8 Flash remains the default model. For more information, see Specifying the model .
Gemini 4 Argon and Gemini 4 Argon Cyber Permissive
Gemini 4 Argon ( gemini-4-argon ) is available in General Availability (GA) . Gemini 4 Argon is Google's frontier model that excels at deep work in complex, real-world tasks across domains including coding, finance, legal, cybersecurity, and science.
On-demand state repartitioning is now generally available
On-demand state repartitioning is now generally available. You can resize the number of shuffle partitions for a stateful Structured Streaming query or Lakeflow pipeline without losing checkpoint state. See On-demand state repartitioning for stateful streaming queries .