SpecterOps Releases Blacklight for AI Agent Endpoint Artifacts
SpecterOps released Blacklight on August 12 as an open-source toolkit for finding and analyzing local artifacts left by Codex, Claude Code, Cursor, and Antigravity CLI. Its discovery loaders rank credential, configuration, and session files before collection, giving security teams a structured way to assess sensitive agent data on Windows, macOS, and Linux endpoints.
SpecterOps released Blacklight on August 12, 2026, as an open-source toolkit for locating and analyzing artifacts created by AI coding agents on user endpoints. The initial catalog covers OpenAI Codex, Anthropic Claude Code, Cursor, and Google's Antigravity CLI across Windows, macOS, and Linux.
What Blacklight maps
The project focuses on local files that may be accessible after an attacker compromises a user's account or workstation. SpecterOps says authentication stores can contain access or refresh tokens, account identifiers, and session metadata. Configuration files may describe trusted projects, sandbox rules, approval settings, environment variables, and Model Context Protocol servers, while transcripts and activity indexes can expose repository names, internal paths, deployment procedures, and the user's recent work.
That distinction matters: this is not a newly disclosed remote vulnerability in Codex, Claude Code, Cursor, or Antigravity. The risk comes from sensitive application state already present within the compromised user's security context. Blacklight is meant to help authorized operators and defenders inventory that state and decide what warrants closer review.
Triage before collection
Blacklight Scout includes loaders for the three major desktop operating systems. The quieter loaders identify agent roots, file metadata, and a small ranked set of recent session candidates without reading artifact bodies. Windows executables can perform deeper metadata analysis, but the project says they are designed not to print credential values, identities, endpoints, or session text.
When deeper analysis is justified, selected artifacts can be processed offline. The session-analysis command recognizes supported formats, produces redacted indicators, and ranks reports for follow-up. The repository also includes osquery configurations and SIEM guidance for defenders. SpecterOps specifically notes that Windows read detection can use Security Event 4663 with Audit File System enabled and appropriate SACLs, while macOS and Linux coverage depends on their available file-event telemetry.
Why it matters for security teams
AI agent profiles are becoming another high-value endpoint data store, alongside browser profiles, shell history, and cloud CLI configuration. For practitioners, the immediate task is not blanket transcript collection. It is to inventory which agents are installed, restrict access to their local state, define retention rules for sessions, and monitor sensitive credential paths with controls appropriate to each operating system. Blacklight turns that assessment into a repeatable workflow while keeping collection selective.
Key Points
- 1Blacklight maps local credential, configuration, project, integration, and session artifacts from Codex, Claude Code, Cursor, and Antigravity CLI.
- 2Its cross-platform Scout loaders prioritize paths and metadata before collection, while deeper session analysis is performed deliberately on selected files.
- 3The release frames AI agent state as endpoint data that security teams should inventory, restrict, retain carefully, and monitor for suspicious access.
Scoring Rationale
The open-source toolkit gives defenders a concrete cross-platform workflow for assessing sensitive coding-agent artifacts. Its operational value is high for developer endpoints, though the exposure requires existing local access rather than a newly disclosed remote flaw.
Sources
Primary source and supporting public references used for this report.
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