Install payload
Install payload is sparse; verify before rollout decisions.
0% (0/3)
Source-backed filter active — add entries to compare trust side by side.
3 results in this view
1 trust signal differs in this sample: Submitter
Signals differ on Submitter — add entries to compare before you install.
Rollout signal scan
Biggest gaps: metadata review, safety notes. 2 entries have 2+ required gaps.
Install payload
Install payload is sparse; verify before rollout decisions.
0% (0/3)
Most at-risk entries in this view
Adoption queue
3/3 visible results are in hold tier and need mitigation before adoption.
2 blockers: Metadata review, Install payload
36/100
Request metadata review from maintainers or internal owners.
Add install/config payload for reproducible team rollout.
Collect package checksum or signed artifact information.
tools/pyrit · trust review · confidence 50%
3 blockers: Metadata review, Safety notes
22/100
Request metadata review from maintainers or internal owners.
Capture safety notes with misuse/guardrail guidance.
Add install/config payload for reproducible team rollout.
tools/promptfoo · trust review · confidence 33%
3 blockers: Metadata review, Safety notes
10/100
Request metadata review from maintainers or internal owners.
Capture safety notes with misuse/guardrail guidance.
Add install/config payload for reproducible team rollout.
tools/garak · trust review · confidence 17%
Decision confidence
3/3 results are low-confidence and need review before adoption.
Hold adoption until Metadata review, Package integrity are resolved.
36/100
tools/pyrit · trust review
Hold adoption until Metadata review, Safety notes are resolved.
22/100
tools/promptfoo · trust review
Hold adoption until Metadata review, Safety notes are resolved.
10/100
tools/garak · trust review
Freshness distribution
Median age 92 days; 1 fresh of 3 scanned. Re-verify the oldest entries.
Oldest entries in this view
Theme distribution
67% of this view shares the top theme. Leading themes: security, ai-red-teaming, open-source.
6 distinct themes across 3 scanned
Open-source prompt testing and red-teaming framework for LLM outputs, regressions, evaluations, and security checks.
Open-source LLM vulnerability scanner for probing model behavior, prompt attack surfaces, and safety failures.
Open-source Python framework from Microsoft for identifying generative AI safety and security risks through automated and human-led red-team assessments.