updated 2026-10-10 20:07 UTC

Openbrowser Ai

Repository Website

OpenBrowser is a framework for intelligent browser automation. It combines direct CDP communication with a CodeAgent architecture, where the LLM writes Python code executed in a persistent namespace, to navigate, interact with, and extract information from web pages autonomously.

Agent Skills Python Listed MIT

Is Openbrowser Ai safe? Promising trust profile, but some evidence still deserves review.

OSSF Scorecard 3.4 / 10
Provenance Attested
Signed commits 27%
Last push 12d ago
Advisories None known
Compare Openbrowser Ai

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In detail: Openbrowser Ai scores 66.3/100 (Grade B), ranked #50 of 371 tracked open-source AI agent projects, on evidence coverage B (3 of 5 independent signal types). The public evidence: its packages ship with cryptographic provenance; OSSF Scorecard rates its supply-chain practices 3.4/10; 27% of recent commits are signed; no published advisory affects its latest release (openbrowser-ai); last pushed 2026-09-28. Every point is earned from checkable signals — never paid placement. How scoring works →

How Openbrowser Ai could raise its score

Each line changes one public signal and recomputes with the live scoring function. The gains don't add up exactly, because the score is capped near the top.

Already done? Suggest a correctionAdd the trust badge

Chain of custody

Scanners check what the code says. This traces who ships Openbrowser Ai and whether that has changed: from the source repository, through how changes are reviewed and released, to the package you install. These are the checks for OWASP ASI04 Agentic Supply Chain Vulnerabilities and, for skills, AST02 Supply Chain Compromise.

  1. Source Partly signed

    github.com/billy-enrizky/openbrowser-ai, MIT, last pushed 2026-09-28. 27% of the last 100 commits carry a verified signature; the rest can't be tied to a verified identity.

  2. Review and release Weak

    OpenSSF Scorecard rates the repository's practices 3.4/10 (scanned Oct 4, 2026). The checks that decide who can get a change released:

    • Code Review0
    • Branch Protection0
    • Signed Releases0
    • Dangerous Workflow10
    • Token Permissions0
    • Pinned Dependencies0
    All 18 Scorecard checks
    Binary-Artifacts 9
    Branch-Protection 0
    CI-Tests 5
    CII-Best-Practices 0
    Code-Review 0
    Contributors 10
    Dangerous-Workflow 10
    Dependency-Update-Tool 0
    Fuzzing 0
    License 10
    Maintained 10
    Packaging 10
    Pinned-Dependencies 0
    SAST 0
    Security-Policy 0
    Signed-Releases 0
    Token-Permissions 0
    Vulnerabilities 0

  3. Published packages Partly attested

    • PyPI openbrowser-ai Source link isn't a GitHub repo Build provenance attested

  4. What you install today No known advisories

    Latest release checked: openbrowser-ai 0.1.54. No published advisory affects it (OSV, checked 2026-10-10).

Changes to this chain

  • 2026-09-23 Package provenance attestation detected
  • 2026-08-31 OSSF Scorecard: 3.4/10

Evidence behind this score

Coverage B: 3 of 5 independent evidence types found.

  • GitHub repository data
  • Package downloads
  • Supply-chain checks
  • Public actions (missing)
  • Community mentions (missing)

Verify this score yourself

Every build re-issues Openbrowser Ai’s score as an Ed25519-signed credential, valid for 7 days. You can check it offline against HVTracker’s published key; if anyone changes a number after signing, verification fails.

Signed credential (JSON) How to verify

What this score doesn’t check

It covers who ships the code, not what the code does. It doesn’t read the skill’s instructions for injected instructions, watch runtime behaviour, or find bugs nobody has disclosed yet. For that, run a content scanner before you install it, such as Cisco Skill Scanner.

How Openbrowser Ai compares in Agent Skills

  1. #48 Tlive 66.5 +0.2
  2. #49 Loop Engineering 66.3 ±0
  3. #50 Openbrowser Ai 66.3 this agent
  4. #51 Herdr 66.2 −0.1
  5. #52 Jscpd 66.1 −0.2

Bars show each HVTrust score; the tick marks Openbrowser Ai’s 66.3.

Where the 66.3 comes from

HVTrust dimensions vs the Agent Skills average

66.3 / 100 · 100.0% confidence

Openbrowser Ai Agent Skills average (371 agents)

Safety / Integrity50% OSSF Scorecard · 30% provenance · 20% signed commits
13.1 / 25
5.3 above avg 7.8
Identity / Provenance60% listing status · 40% build provenance
18.0 / 18
6.6 above avg 11.4
Transparency50% declared license · 50% OSSF Scorecard
11.4 / 17
0.6 below avg 12.0
Maintenance60% last-push freshness · 40% commit activity
17.8 / 20
3.7 above avg 14.1
AdoptionLog-scaled stars · package downloads
8.9 / 20
in line with avg 9.0

Quick Trust Read

What Would Improve It
Increase the share of verified signed commits for clearer maintainer identity.
Recent Changes
2026-09-23
Tool Surface Changed
Detected tool/plugin surface changed: none → declared
2026-09-23
Provider Added
Runtime surface grew — new detected provider dependencies: Amazon Bedrock, Anthropic, Azure OpenAI, Google Gemini, Groq, Multi-provider (LiteLLM), OpenAI, Postgres, Redis
2026-09-23
Mcp Status Changed
Detected MCP server support changed: none → implemented
Maintainer Checklist
Raise Scorecard signals Current OSSF Scorecard is 3.4/10. Tighten the weakest checks to improve public safety evidence.
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 Openbrowser Ai View Agent Skills Report missing data
65.4
Activity sub-score · out of 100
#50
In Agent Skills

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade B reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage B is separate — it grades how many independent signal types back the score (3 of 5), so a high score on thin evidence stays visible. Full methodology →

Signals refreshed 2026-10-10 20:07 UTC · Repo last pushed 12 days ago

Rank Trend

2026-09-29 2026-10-10

Activity & Reach

Stars
275
Forks
29
Last Push
2026-09-28
12 days ago
Commits (4 wk)
44
Downloads (7d)
190
pypi
HN mentions (30d)
—
Open Issues
1
Rank Change
▼1
was #49

Analysis

Activity Inputs

65.4 / 100
StarsRepository reach
14.6 / 30
FreshnessLast push recency
23.3 / 25
ActivityRecent commits
20.6 / 25
CommunityFork signal
6.9 / 20

Common questions about Openbrowser Ai

Openbrowser Ai has a mixed signal profile. Some trust indicators are present, others are missing. Whether it is safe for your use case depends on which gaps matter to you — review the breakdown below before adopting in production.
Does Openbrowser Ai publish package provenance?
Yes. Openbrowser Ai's package releases carry build provenance attestations, which cryptographically link the published package back to its source repository and CI workflow.
Does Openbrowser Ai have an OpenSSF Scorecard?
Openbrowser Ai has an OpenSSF Scorecard score of 3.4/10. The Scorecard checks for branch protection, signed releases, dependency updates, fuzzing, code review, and other supply-chain hygiene items. See the full check breakdown on this page.
Is Openbrowser Ai actively maintained?
Maintained. Last push was 12 days ago.
What license does Openbrowser Ai use?
Openbrowser Ai ships under MIT. A declared, OSI-approved license is one of the transparency signals HVTrust scores.
Are Openbrowser Ai's commits signed?
27% of the last 100 commits to Openbrowser Ai are verified-signed (GPG, SSH, S/MIME, or GitHub's signing flow). Signed commits help confirm that code was authored by who the commit claims.

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
high confidence
Implemented
Openbrowser Ai appears to expose MCP server capabilities.
Detailed evidence is not shown in the public view.
External Service Dependencies
high confidence
9 detected
Public provider/service dependencies detected.
Credential signal: API keys or service config markers documented.
Tool / Plugin Surface
high confidence
Declared
Declared plugin/integration surface detected.
  • browser
  • database
Detailed evidence is not shown in the public view.
Package Provenance Drift
low confidence
Unknown
Package source metadata is missing or inconclusive
Detailed evidence is not shown in the public view.
  • MCP signal live
  • External deps live
  • Tool / plugin surface live
  • Package provenance drift live
How this surface has changed

Detected changes to Openbrowser Ai's runtime surface and supply-chain posture, from daily public-signal snapshots. A change here means our detectors see something different — a genuinely changed capability, or better evidence of an existing one.

2026-09-23
Tool Surface Changed
Detected tool/plugin surface changed: none → declared
2026-09-23
Provider Added
Runtime surface grew — new detected provider dependencies: Amazon Bedrock, Anthropic, Azure OpenAI, Google Gemini, Groq, Multi-provider (LiteLLM), OpenAI, Postgres, Redis
2026-09-23
Mcp Status Changed
Detected MCP server support changed: none → implemented
2026-09-23
Provenance Added
Package provenance attestation detected

Maintain Openbrowser Ai?

For maintainers

HVTrust scores Openbrowser 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
Rank 8HVTrust 3Listed 2Grade 2Scorecard 1Score 1Delisted 1Provenance 1MCP 1Surface 1Surface 1
2026-09-23
Tool Surface Changed
Detected tool/plugin surface changed: none → declared
2026-09-23
Provider Added
Runtime surface grew — new detected provider dependencies: Amazon Bedrock, Anthropic, Azure OpenAI, Google Gemini, Groq, Multi-provider (LiteLLM), OpenAI, Postgres, Redis
2026-09-23
Mcp Status Changed
Detected MCP server support changed: none → implemented
2026-09-23
Provenance Added
Package provenance attestation detected
2026-09-23
Grade Changed
Trust grade D → B
2026-09-23
Rank Moved
Rank rose 247 spots (#290 → #43)
2026-09-23
HVTrust Changed
HVTrust up 40.0pts (27.5 → 67.5)
2026-09-22
Newly Listed
First tracked at rank #290
2026-09-21
Removed From Active Tracking
Removed from active tracking
2026-09-20
Rank Moved
Rank rose 81 spots (#154 → #73)
2026-09-20
HVTrust Changed
HVTrust up 7.3pts (55.1 → 62.4)
2026-09-20
Activity Score Changed
Activity score up 24pts (35 → 59)
2026-09-05
Rank Moved
Rank dropped 16 spots (#100 → #116)
2026-08-31
Scorecard Added
OSSF Scorecard: 3.4/10
2026-08-31
Grade Changed
Trust grade D → C
2026-08-31
Rank Moved
Rank rose 44 spots (#124 → #80)
2026-08-31
HVTrust Changed
HVTrust up 7.2pts (49.2 → 56.4)
2026-08-30
Rank Moved
Rank dropped 24 spots (#100 → #124)
2026-08-29
Rank Moved
Rank dropped 18 spots (#82 → #100)
2026-08-28
Rank Moved
Rank dropped 18 spots (#64 → #82)
2026-08-27
Rank Moved
Rank dropped 17 spots (#47 → #64)
2026-08-26
Newly Listed
First tracked at rank #47
GitHub → Website → PyPI: openbrowser-ai

Embed Badge Badge guide for maintainers →

For maintainers
HVTrust 66.3 Grade B
Markdown:
[![HVTrust](https://hvtracker.net/badge/openbrowser-ai.svg)](https://hvtracker.net/agents/openbrowser-ai)
HTML:
<a href="https://hvtracker.net/agents/openbrowser-ai"><img src="https://hvtracker.net/badge/openbrowser-ai.svg" alt="HVTrust"></a>

Other agents in Agent Skills

Data sources
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance) · OpenSSF Scorecard CLI
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.4 · Raw JSON