Open Deep Research (dzhng)

An AI-powered research assistant that performs iterative, deep research on any topic by combining search engines, web sc

Research & Data TypeScript Grade D Listed MIT
38.0/100
Rank #384 of 468
Compare Open Deep Research (dzhng)

Thin or incomplete trust evidence. Review carefully before production use.

Open compare tool Suggest correction
Listing state
Listed
Evidence coverage
Grade C · 2/5 signals
Last push
2026-04-11 · 117d ago
Recent change
No recent signal change

Is Open Deep Research (dzhng) safe? Open Deep Research (dzhng) scores 38.0/100 (Grade D), ranked #384 of 468 tracked open-source AI agent projects, on evidence coverage C (2 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 1.8/10; 40% of recent commits are signed; last pushed 2026-04-11. Every point is earned from checkable signals — never paid placement. How scoring works →

Ranked neighbours in Research & Data

Quick Trust Read

What Would Improve It
Publish package provenance or release attestations for stronger supply-chain evidence.
Recent Changes
2026-07-29
Rank Moved
Rank dropped 10 spots (#374 → #384)
2026-07-15
Rank Moved
Rank dropped 25 spots (#338 → #363)
2026-07-14
Rank Moved
Rank dropped 18 spots (#320 → #338)
Maintainer Checklist
Raise Scorecard signals Current OSSF Scorecard is 1.8/10. Tighten the weakest checks to improve public safety evidence.
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.
Refresh maintenance signals The repo was last pushed 117 days ago. Fresh activity helps separate stable projects from stale ones.
49.9
Activity sub-score · out of 100
#18

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 C is separate — it grades how many independent signal types back the score (2 of 5), so a high score on thin evidence stays visible. Full methodology →

Signals refreshed 2026-08-06 05:00 UTC · Repo last pushed 117 days ago

Rank Trend

2026-07-05 2026-08-06

Activity & Reach

Stars
19.5k
Forks
2.0k
Last Push
2026-04-11
117 days ago
Commits (4 wk)
0
Downloads (7d)
HN mentions (30d)
Open Issues
72
Rank Change
=
was #384

Analysis

HVTrust Dimensions vs Research & Data

38.0 / 100 · 100.0% confidence

Open Deep Research (dzhng) Research & Data average (24 agents)

Safety / Integrity50% OSSF Scorecard · 30% provenance · 20% signed commits
4.3 / 25
3.7 below avg 8.0
Identity / Provenance60% listing status · 40% build provenance
10.8 / 18
0.9 below avg 11.7
Transparency50% declared license · 50% OSSF Scorecard
10.0 / 17
1.7 below avg 11.7
Maintenance60% last-push freshness · 40% commit activity
4.2 / 20
8.3 below avg 12.5
AdoptionLog-scaled stars · package downloads
10.3 / 20
1.5 below avg 11.8

Activity Inputs

49.9 / 100
StarsRepository reach
25.7 / 30
FreshnessLast push recency
8.8 / 25
ActivityRecent commits
0.0 / 25
CommunityFork signal
15.3 / 20

Supply Chain Trust

Package Provenance
None
No package attestations found
OSSF Scorecard
1.8 / 10
OpenSSF Scorecard · scanned Aug 4, 2026
Signed Commits
40%
of last 100 commits verified
Binary-Artifacts 10
Branch-Protection 0
CI-Tests 0
CII-Best-Practices 0
Code-Review 3
Contributors 6
Dangerous-Workflow -1
Dependency-Update-Tool 0
Fuzzing 0
License 10
Maintained 0
Packaging -1
Pinned-Dependencies 0
SAST 0
Security-Policy 0
Signed-Releases -1
Token-Permissions -1
Vulnerabilities 0

Is Open Deep Research (dzhng) safe?

Public trust evidence for Open Deep Research (dzhng) 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 Open Deep Research (dzhng) publish package provenance?
No published build provenance is currently detected for Open Deep Research (dzhng). This is common for open-source projects but means consumers cannot independently verify that the package on the registry matches the GitHub source.
Does Open Deep Research (dzhng) have an OpenSSF Scorecard?
Open Deep Research (dzhng) has an OpenSSF Scorecard score of 1.8/10. 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 Open Deep Research (dzhng) actively maintained?
Slowing down. Last push was 117 days ago — keep an eye on whether activity resumes.
What license does Open Deep Research (dzhng) use?
Open Deep Research (dzhng) ships under MIT. A declared, OSI-approved license is one of the transparency signals HVTrust scores.
Are Open Deep Research (dzhng)'s commits signed?
40% of the last 100 commits to Open Deep Research (dzhng) 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
None detected
No MCP server signal detected.
Detailed evidence is not shown in the public view.
External Service Dependencies
high confidence
3 detected
Public provider/service dependencies detected.
Credential signal: No explicit API-key/config marker detected.
Tool / Plugin Surface
high confidence
2 tags
Broad capability areas detected.
  • code
  • search
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
How this surface has changed

Detected changes to Open Deep Research (dzhng)'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.

2026-07-10
Activity Went Stale
No commits for 90 days

Maintain Open Deep Research (dzhng)?

For maintainers

HVTrust scores Open Deep Research (dzhng) 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.

Reputation Timeline

Signal history
Rank 8Listed 1HVTrust 1Scorecard 1Stale 1
2026-07-29
Rank Moved
Rank dropped 10 spots (#374 → #384)
2026-07-15
Rank Moved
Rank dropped 25 spots (#338 → #363)
2026-07-14
Rank Moved
Rank dropped 18 spots (#320 → #338)
2026-07-13
Rank Moved
Rank dropped 36 spots (#284 → #320)
2026-07-10
Activity Went Stale
No commits for 90 days
2026-06-24
Rank Moved
Rank dropped 32 spots (#238 → #270)
2026-06-23
Rank Moved
Rank dropped 18 spots (#220 → #238)
2026-06-22
Rank Moved
Rank dropped 12 spots (#208 → #220)
2026-06-21
Scorecard Added
OSSF Scorecard: 1.8/10
2026-06-21
Rank Moved
Rank rose 53 spots (#261 → #208)
2026-06-21
HVTrust Changed
HVTrust up 23.2pts (19.5 → 42.7)
2026-06-20
Newly Listed
First tracked at rank #261

Embed Badge Badge guide for maintainers →

For maintainers
HVTrust 38.0 Grade D
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Other agents in Research & Data

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