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OpenCV Python

The world's most popular computer vision library with Python bindings — image processing, video, and ML pipelines.

@ai-supply
Installs411k
⟳ upstream 93 · updated 25d ago
↗ Source repository
← More Vision & ImageVision & Image leaderboard →How we grade security →Source ↗
✓ Grade A · 100/100 · SafeSecurity assessment
✓No compromise signals12capabilities surfaced11of 20 OWASP controls clear
External endpoints declaredSuspicious network referencesExternal endpoints declaredExternal endpoints declared
scanned 16d ago·osv · gitleaks · opengrep · picklescan + heuristics·full breakdown in the Security tab ↓

OpenCV Python

opencv-python provides unofficial pre-built OpenCV packages for Python, making the world's most widely used computer vision library trivially installable. OpenCV covers the full spectrum from classical image processing to deep neural network inference, and is the backbone of countless production vision systems.

Key Features

  • 2500+ optimised algorithms: filters, transforms, feature detectors (SIFT, ORB), optical flow
  • Camera calibration, stereo vision, and 3D reconstruction
  • Built-in DNN module: run ONNX, TensorFlow, PyTorch, and Caffe models directly
  • Video I/O: read/write files, RTSP streams, and webcams with a unified API
  • GPU acceleration via CUDA backend; OpenCL support on mobile and embedded

Quick Start

pip install opencv-python
import cv2

img = cv2.imread("image.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
edges = cv2.Canny(blurred, 50, 150)
cv2.imwrite("edges.jpg", edges)
npx ai-supply add opencv-python-vision

Curated mirror of the open-source OpenCV (MIT). Get it from the source.

Rating rank
#1
of 12 in Vision & Image
Install rank
#3
of 12 in Vision & Image
Security score
100/100 · A
safe
Security rank
#1
of 12 in Vision & Image
Installs
411k
cat avg 279k
This listing vs category average
Installs
this
cat avg
Security (of 100)
this
cat avg
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See the Vision & Image leaderboard →
✓ Security: Safe · 100100/100 · grade Ascanned 16d ago
✓ no compromise signals12 risk-surface · 3/20 OWASP controls flagged

Compromise signals — malicious or tampered code (leaked secrets, backdoors, a dropped executable) — reduce the score, and known dependency CVEs carry a bounded penalty (they warrant review but never QUARANTINE — update the dependency to clear). Other dangerous-by-capability traits are risk surface, expected for some capabilities. Every finding is mapped to its OWASP control below.

What this capability can do · med confidence (static)
⚑ filesystem⚑ shell⚑ secrets
egress → answers.opencv.org, stackoverflow.com, docs.opencv.org, pypi.tuna.tsinghua.edu.cn, help.github.com, static.pepy.tech, pepy.tech, www.microsoft.com +11
14 scripts

Findings mapped to the OWASP Top 10 for LLM Applications (2025) and the OWASP Machine Learning Security Top 10. Expand any flagged control for the exact findings — compromise reduces the score; expected/risk-surface do not, except a known CVE, which carries a small bounded penalty (high/critical → Review).

OWASP Top 10 for LLM Applications
⚠LLM05Improper Output Handlinghigh
Code that pipes model/user output into shell, eval, SQL or paths unsafely.
•Suspicious code patterns — destructive rm -rf / · opencv-opencv-python-ed685ab/docker/musllinux_1_2/Dockerfile_aarch64 (CWE-78)risk surface
•Suspicious code patterns — OS command execution · opencv-opencv-python-ed685ab/find_version.py (CWE-78)risk surface
•Suspicious code patterns — dynamic code execution · opencv-opencv-python-ed685ab/setup.py (CWE-95)risk surface
⚠LLM06Excessive Agencylow
Over-broad tool/permission surface or unrestricted egress.
•External endpoints declared — 4 distinct host(s) · opencv-opencv-python-ed685ab/.github/issue_template.mdrisk surface
•External endpoints declared — 1 distinct host(s) · opencv-opencv-python-ed685ab/.github/workflows/build_wheels_macos.ymlrisk surface
•External endpoints declared — 3 distinct host(s) · opencv-opencv-python-ed685ab/CONTRIBUTING.mdrisk surface
•External endpoints declared — 7 distinct host(s) · opencv-opencv-python-ed685ab/LICENSE-3RD-PARTY.txtrisk surface
•External endpoints declared — 10 distinct host(s) · opencv-opencv-python-ed685ab/README.mdrisk surface
•External endpoints declared — 6 distinct host(s) · opencv-opencv-python-ed685ab/docker/manylinux2014/Dockerfile_i686risk surface
•External endpoints declared — 8 distinct host(s) · opencv-opencv-python-ed685ab/docker/manylinux_2_28/Dockerfile_aarch64risk surface
•External endpoints declared — 2 distinct host(s) · opencv-opencv-python-ed685ab/scripts/build.shrisk surface
§LLM09MisinformationGovernance
Artifacts designed to produce false/deceptive output.
Detectable only by runtime behavioral evaluation; addressed via responsible-use attestation.
◷LLM10Unbounded ConsumptionRuntime-enforced
Unbounded loops/recursion causing DoS or runaway cost.
Enforced at runtime by the gateway (rate limits + spend caps + size caps); static check flags unbounded loops.
✓LLM01Prompt InjectionPassed
✓LLM02Sensitive Information DisclosurePassed
✓LLM03Supply ChainPassed
✓LLM04Data and Model PoisoningPassed
Backdoors/poisoning in training data or serialized models.
Behavioral poisoning needs model execution; static check covers unsafe serialization + dataset skew only.
✓LLM07System Prompt LeakagePassed
✓LLM08Vector and Embedding WeaknessesPassed
PII or plaintext source leakage in embedding/vector exports.
Embedding inversion/poisoning is largely runtime; static check covers PII in vector exports.
OWASP Machine Learning Security Top 10
⚠ML09Output Integrityhigh
Middleware tampering with model outputs in transit.
Gateway enforces TLS + response integrity; static check flags output-rewriting code.
•Suspicious code patterns — destructive rm -rf / · opencv-opencv-python-ed685ab/docker/musllinux_1_2/Dockerfile_aarch64 (CWE-78)risk surface
•Suspicious code patterns — OS command execution · opencv-opencv-python-ed685ab/find_version.py (CWE-78)risk surface
•Suspicious code patterns — dynamic code execution · opencv-opencv-python-ed685ab/setup.py (CWE-95)risk surface
§ML01Input Manipulation (Adversarial)Governance
Models vulnerable to adversarial perturbations.
Requires runtime robustness evaluation; addressed via publisher robustness attestation.
§ML03Model InversionGovernance
Training data reconstructable from a model's outputs.
Runtime/evaluation property; addressed via model-card data-provenance + DP attestation.
§ML04Membership InferenceGovernance
Determining whether a record was in the training set.
Runtime/evaluation property; addressed via overfitting disclosure + DP attestation.
§ML08Model SkewingGovernance
Models trained on skewed data producing biased output.
Requires fairness evaluation; addressed via model-card bias/limitations disclosure.
✓ML02Data PoisoningPassed
Poisoned training datasets with triggers or anomalous distributions.
Static check covers trigger phrasing, PII and label skew; full poisoning detection is runtime.
✓ML05Model TheftPassed
Unlicensed re-distribution / license-incompatible derivatives.
Static check verifies license declaration; extraction throttling is runtime.
✓ML06AI Supply ChainPassed
✓ML07Transfer Learning AttackPassed
Backdoored base models / LoRA adapters propagating to derivatives.
Backdoor detection needs behavioral probing; static check covers unsafe serialization + provenance.
✓ML10Model Poisoning (Weights)Passed
Tampered model weight files; integrity must be verifiable.
Static check enforces safe formats + records a content hash for downstream verification.
Other findings (5) · hygiene / uncategorized
•Suspicious network references — suspicious TLD (2 URLs) · opencv-opencv-python-ed685ab/.github/workflows/build_wheels_macos.ymlrisk surface
•Unrecognized file type — '.gitignore' is not on the allowlist · opencv-opencv-python-ed685ab/.gitignorerisk surface
•Unrecognized file type — '.gitmodules' is not on the allowlist · opencv-opencv-python-ed685ab/.gitmodulesrisk surface
•Unrecognized file type — '.in' is not on the allowlist · opencv-opencv-python-ed685ab/MANIFEST.inrisk surface
•Unrecognized file type — '.?' is not on the allowlist · opencv-opencv-python-ed685ab/docker/manylinux1/Dockerfile_i686risk surface
✔ verified source · pinned opencv-opencv-python-ed685ab
Check against a policy

The same gate an agent runs before installing (POST /api/v1/trust/opencv-python-vision/check). Click a policy:

Consume OpenCV Python programmatically. Authenticate with an API key or session — see Authorize an agent.

# Agents: CHECK BEFORE YOU INSTALL (no auth) — score, grade, level, capability manifest
curl https://ai-supply.store/api/v1/trust/opencv-python-vision

# Gate against your org policy (returns { pass, violations })
curl -X POST https://ai-supply.store/api/v1/trust/opencv-python-vision/check \
  -H "Content-Type: application/json" \
  -d '{"minGrade":"B","denyPermissions":["shell"],"denyUnknownEgress":true}'

# CLI
npx ai-supply add opencv-python-vision

# REST (install → download)
curl -X POST https://ai-supply.store/api/v1/listings/opencv-python-vision/install \
  -H "Authorization: Bearer $AIM_KEY"

# MCP tool
install_listing({ "slug": "opencv-python-vision" })
OpenAPI spec →
vlatest
✓ Security: Safe · 1001mo ago

Curated mirror — latest upstream source. See the repository for tagged releases.

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