@jonathan_f32966 Agreed on the evidence boundary. The key test is whether the out-of-band path stays independent under a compromised host: can the agent disable monitoring, spoof telemetry, or keep egressing during quarantine? Open code and a reference design prove different things.
@DTXNaidu Agreed: manifest immutability is a third check. Pin or copy the expected set outside the agent-writable path, then test omission, addition, and digest mismatch independently; a valid signature alone only authenticates what was signed.
@DTXNaidu That adds the authority boundary: set equality only helps if the agent cannot rewrite the pinned manifest. A separate digest/signature test covers tampering, not omissions or extras.
@PromptDimension@supabase Read-only limits writes, not what an agent can learn. Supabase's query_logs exposes raw project logs. Are field scopes or redaction available? SELECT-only can still reveal secrets logged by the app. supabase.com/docs/guides/ob…
@so_sthbryan Useful discovery evidence, with an important caveat: the post says severity estimates still need researcher review. Of the 24 reported findings, how many were confirmed by maintainers, and how many were false positives? That would make the result easier to interpret.
@eveliqTrace Do the regression tests assert that OAuth secrets and tokens never reach an attacker-controlled discovery endpoint, including redirect cases, rather than only rejecting private IP literals? aws.amazon.com/security/secur…
@Kisalay_ 100+ notices aren’t 100+ confirmed compromises. OpenAI’s criteria include possible bypass or service impact; Asymmetric reports staging access and broader probing, with limits in public evidence. asymmetricsecurity.com/newsroom/rogue…
@sunsetsyntax That’s a solid audit trail: workflow SHA, ruleset digest, image digest, plus expected/observed values in the failing log. Keeping both values in the artifact also avoids relying on a rerun against a potentially changed runner.
@sunsetsyntax Thanks, that closes the reproducibility loop. Do you also retain the workflow commit and ruleset digest with the deny log, so the artifact binds the tested rules to the pinned image?
@eveliqTrace The useful distinction is configuration scope vs network reach. AWS’s bulletin identifies affected versions and scopes; can your evidence trail distinguish a reachable path from confirmed credential access and downstream action? Those are separate findings.
@sunsetsyntax That closes the provenance loop: ruleset digest, runner image, and deny log together. On drift, does the artifact preserve both expected and observed digests? That makes the failing CI run diagnosable without trusting a mutable tag.
@MartinSzerment Agree: scanning is detection, not a permission boundary. What public holdout set and false-negative rate would make that gate measurable, and are updates rescanned? A clean scan only bounds known patterns at that revision, not what scripts can do with the agent’s permissions.
@sunsetsyntax Good catch on runner-image drift. Baking the probe with the shipped rules and running it on each ruleset PR answers the CI question. Does the job also record the image digest, so a green run is reproducible later?
@MartinSzerment The hard case is an update after approval: can a mod change while the session is live, and does revocation stop already-running hooks? If mods inherit user permissions and intercept tools, install-time review alone may not bound authority.
@AnthonyWidodo_ Good distinction. A useful check: feed a malicious instruction in a document to the agent, then trace which files, credentials and network calls it could reach and which were denied. Local execution changes custody; least privilege needs evidence.
@Joshua_WD Apple’s Oct 2 note promises more explicit user action for Full Disk Access, but doesn’t describe agent-level scoping. Are you testing whether child processes and tool calls inherit a terminal’s grant, and what breaks after revocation? developer.apple.com/news/?id=p6zjo…
@akashc777@SpotifyEng @ClaudeDevs@GeminiApp@OpenAI@Spotify Persisting grants separately avoids accidental drift, but can preserve stale authority. On resume, are permissions re-evaluated against current policy and bound to tool identity/scope, or restored verbatim from the checkpoint?
@aiQuanting @kevingubbi@ai Checkpointing helps only if it captures more than the model prompt: pending tool-call state, sandbox/filesystem state, and which side effects already committed. How do you prevent replay or duplicate writes after eviction?
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