
Anthropic has launched OSS Scanner, a free service that uses its strongest AI models, including Mythos, to perform periodic security scans on opt-in open-source projects. The system generates vulnerability reports automatically without human review, aiming to provide faster and more frequent detection than traditional methods. While this approach offers significant defensive advantages by leveraging large-scale model capabilities, it carries the risk of incorrect or invalid reports due to the lack of human triage. This initiative follows recent incidents where AI-generated bug reports overwhelmed maintainers in major projects like Linux.
Read originalEarlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
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This release tightens the leash on Claude Code's autonomous capabilities while fixing critical sandbox escapes. The new effort parameter for Agent tools lets developers explicitly control sub-agent depth, a necessary guardrail as these systems grow more complex. Security fixes are prominent, addressing how plugins handle network paths and how file permissions persist during session resumption. It’s a stability patch that ensures the tool remains usable in enterprise environments without compromising on the new agent features.
Anthropic quietly shipped a significant model update alongside routine maintenance. Claude Haiku 5.5 is now the default on the API, offering a 1M context window at $0.10 per million tokens, which lowers the cost floor for high-volume coding tasks. The release also patches critical stability issues in the local agent runtime, specifically fixing memory leaks in HTTP MCP connections and resolving session state corruption during context compaction. These fixes matter because they stabilize the autonomous coding workflow that developers rely on daily. With Haiku 5.5 now standard, teams can deploy cheaper, faster iterations without manual configuration.
Anthropic quietly patched a frustrating edge case in Claude Code’s agent hooks. Previously, instructions like 'Block commands that...' were often ignored because the model didn't recognize them as valid blocking criteria. This update ensures those prompts are properly interpreted, while also refining how stop conditions are judged to prevent premature termination. It’s a small but necessary fix for anyone relying on strict guardrails in automated coding workflows.