updated 2026-08-06 17:00 UTC

pentest-ai

0xSteph/pentest-ai

Pending first signal refresh

Security & Guardrails Python Grade D Listed
16.8/100
Rank #500 of 522
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Thin or incomplete trust evidence. Review carefully before production use.

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Listing state
Listed
Evidence coverage
Grade D · 1/5 signals
Last push
2026-08-06 · 0d ago
Recent change
New

Is pentest-ai safe? pentest-ai scores 16.8/100 (Grade D), ranked #500 of 522 tracked open-source AI agent projects, on evidence coverage D (1 of 5 independent signal types). The public evidence: no package-provenance attestation found; no OSSF Scorecard result yet; recent commits are unsigned; last pushed 2026-08-06. Every point is earned from checkable signals — never paid placement. How scoring works →

Ranked neighbours in Security & Guardrails

#13 T3MP3ST — 24.9 (D) → #14 CyberStrike — 24.6 (D) → #15 AutoCVE — 17.4 (D) → #16 auto-re-agent — 16.9 (D) →

Quick Trust Read

What Would Improve It
Add or improve OSSF Scorecard coverage so safety checks are easier to verify.
Recent Changes
2026-08-06
Newly Listed
First tracked at rank #500
Maintainer Checklist
Add Scorecard coverage Expose the repository to OpenSSF Scorecard checks so supply-chain posture is easier to verify.
Publish provenance Add package provenance or release attestations so users can verify where shipped artifacts came from.
Increase signed commits Raise the share of verified-signed commits to make maintainer identity and release history easier to trust.
Compare with another agent Get email alerts for pentest-ai View Security & Guardrails Report missing data
65.4
Activity sub-score · out of 100
#17
In Security & Guardrails

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade D reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage D is separate — it grades how many independent signal types back the score (1 of 5), so a high score on thin evidence stays visible. Full methodology →

Signals refreshed 2026-08-06 17:00 UTC · Repo last pushed today

Activity & Reach

Stars
1.6k
Forks
302
Last Push
2026-08-06
today
Commits (4 wk)
5
Downloads (7d)
—
HN mentions (30d)
—
Open Issues
4
Rank Change
NEW

Analysis

HVTrust Dimensions vs Security & Guardrails

16.8 / 100 · 50.0% confidence

pentest-ai Security & Guardrails average (17 agents)

Safety / Integrity50% OSSF Scorecard · 30% provenance · 20% signed commits
0 / 25
7.4 below avg 7.4
Identity / Provenance60% listing status · 40% build provenance
10.8 / 18
in line with avg 11.2
Transparency50% declared license · 50% OSSF Scorecard
0 / 17
10.2 below avg 10.2
Maintenance60% last-push freshness · 40% commit activity
15.1 / 20
1.4 below avg 16.5
AdoptionLog-scaled stars · package downloads
7.7 / 20
2.5 below avg 10.2

Activity Inputs

65.4 / 100
StarsRepository reach
19.2 / 30
FreshnessLast push recency
25.0 / 25
ActivityRecent commits
9.7 / 25
CommunityFork signal
11.5 / 20

Supply Chain Trust

Package Provenance
None
No package attestations found
OSSF Scorecard
—
Not available
Signed Commits
—
Unable to query

Is pentest-ai safe?

Public trust evidence for pentest-ai is thin: several supply-chain signals are missing or weak. This does not mean the project is unsafe — it means an outside observer cannot easily verify the usual integrity checks. Treat with extra scrutiny.
Does pentest-ai publish package provenance?
No published build provenance is currently detected for pentest-ai. This is common for open-source projects but means consumers cannot independently verify that the package on the registry matches the GitHub source.
Does pentest-ai have an OpenSSF Scorecard?
No OpenSSF Scorecard data is currently published for pentest-ai. Maintainers can enable the Scorecard GitHub Action to get a public score; without it, automated supply-chain hygiene is harder for outsiders to verify.
Is pentest-ai actively maintained?
Actively maintained. The repository was pushed to within the last 1 day(s).
What license does pentest-ai use?
pentest-ai ships under no SPDX license detected. A declared, OSI-approved license is one of the transparency signals HVTrust scores.

Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.

AI agent surface

MCP, providers, tool surface
Scored in HVTrust

These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →

MCP Server Support
None detected
No MCP server signal detected.
Detailed evidence is not shown in the public view.
External Service Dependencies
None detected
No clear third-party provider dependency detected.
Credential signal: No explicit API-key/config marker detected.
Tool / Plugin Surface
None detected
No clear plugin system or broad tool surface detected.
Detailed evidence is not shown in the public view.
Package Provenance Drift
N/A
No package source configured
Detailed evidence is not shown in the public view.
  • MCP signal live
  • External deps live
  • Tool / plugin surface live
  • Package provenance drift live

Maintain pentest-ai?

For maintainers

HVTrust scores pentest-ai from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.

Submit a correction → Add the trust badge

Reputation Timeline

Signal history
Listed 1
2026-08-06
Newly Listed
First tracked at rank #500
GitHub →

Embed Badge Badge guide for maintainers →

For maintainers
HVTrust 16.8 Grade D
Markdown:
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HTML:
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Other agents in Security & Guardrails

Data sources
GitHub REST API (repo, commits, stars, forks, license)
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.2 · Raw JSON