Skip to content
ai-supply.store
探すカテゴリランキングコミュニティAgent APIFAQ
サインイン無料登録
catalog / Coding / GPT Engineer
◉AgentCodingFree

GPT Engineer

Conversational AI coding agent that builds entire codebases from natural-language specs with one prompt.

@ai-supply
インストール数592k
⟳ upstream v0.3.1 · updated 2y ago
↗ ソースリポジトリ
← More CodingCoding leaderboard →How we grade security →Source ↗
! Grade B · 75/100 · ReviewSecurity assessment
✓No compromise signals17capabilities surfaced1known CVE7of 20 OWASP controls clear
External endpoints declaredExternal endpoints declaredExternal endpoints declaredExternal endpoints declared
scanned 18d ago·osv · gitleaks · opengrep · picklescan + heuristics·full breakdown in the Security tab ↓

GPT Engineer

GPT Engineer turns a plain-English project description into a working codebase. It prompts you for clarifications, generates all necessary files, and can iteratively improve the code through a feedback loop — all from the command line.

Key Features

  • Full-project generation — produces complete, runnable codebases (not just snippets) from a single spec file
  • Clarification loop — asks targeted questions before generating to reduce ambiguity
  • Improve mode — run it on an existing repo to add features or fix bugs
  • Benchmarked — evaluated on HumanEval and SWE-bench style tasks
  • Provider agnostic — supports OpenAI, Anthropic, Azure OpenAI, and local models via LM Studio / Ollama
  • Lightweight — no heavy orchestration framework; pure Python with minimal dependencies

Quick Start

pip install gpt-engineer
gpt-engineer projects/my-new-app

Create projects/my-new-app/prompt with:

Build a FastAPI web app with a /health endpoint and SQLite persistence for user notes.

Install via ai-supply

npx ai-supply add gpt-engineer-code-generator

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

Rating rank
#1
of 27 in Coding
Install rank
#2
of 27 in Coding
Security score
75/100 · B
review
Security rank
#19
of 27 in Coding
Installs
592k
cat avg 157k
This listing vs category average
Installs
this
cat avg
Security (of 100)
this
cat avg
Adoption trend
See the Coding leaderboard →
! Security: Review · 7575/100 · grade Bscanned 18d ago
✓ no compromise signals18 risk-surface · 8/20 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⚑ network⚑ secrets
egress → www.contributor-covenant.org, pre-commit.com, black.readthedocs.io, beta.ruff.rs, git-scm.com, docs.sweep.dev, gpt-engineer.readthedocs.io, codecov.io +27

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
⚠LLM03Supply Chaincritical
Vulnerable/compromised dependencies, models or archives in the artifact.
•Dependency manifest — 1 pip requirements declared · AntonOsika-gpt-engineer-a90fcd5/projects/example-improve/requirements.txtrisk surface
•Vulnerable dependencies — 184 known vulnerabilities in: aiohttp@3.9.5, black@23.3.0, bleach@6.1.0, filelock@3.13.4, h11@0.14.0, idna@3.7, jinja2@3.1.3, jupyter-core@5.7.2 (CWE-1395)known CVE · -25 pts
⚠LLM05Improper Output Handlinghigh
Code that pipes model/user output into shell, eval, SQL or paths unsafely.
•Suspicious code patterns — destructive rm -rf / · AntonOsika-gpt-engineer-a90fcd5/docker/Dockerfile (CWE-78)risk surface
•Suspicious code patterns — world-writable chmod 777 · AntonOsika-gpt-engineer-a90fcd5/docker/entrypoint.sh (CWE-732)risk surface
•Suspicious code patterns — OS command execution · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/applications/cli/file_selector.py (CWE-78)risk surface
•Suspicious code patterns — dynamic code execution · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/core/project_config.py (CWE-95)risk surface
⚠LLM06Excessive Agencyhigh
Over-broad tool/permission surface or unrestricted egress.
•External endpoints declared — 1 distinct host(s) · AntonOsika-gpt-engineer-a90fcd5/.dockerignorerisk surface
•External endpoints declared — 2 distinct host(s) · AntonOsika-gpt-engineer-a90fcd5/.github/CODE_OF_CONDUCT.mdrisk surface
•External endpoints declared — 5 distinct host(s) · AntonOsika-gpt-engineer-a90fcd5/.github/CONTRIBUTING.mdrisk surface
•External endpoints declared — 11 distinct host(s) · AntonOsika-gpt-engineer-a90fcd5/README.mdrisk surface
•External endpoints declared — 3 distinct host(s) · AntonOsika-gpt-engineer-a90fcd5/docs/installation.rstrisk surface
•External endpoints declared — 8 distinct host(s) · AntonOsika-gpt-engineer-a90fcd5/docs/open_models.mdrisk surface
•Broad capability surface — 3 high-impact capability categories referenced — verify least-privilege · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/applications/cli/file_selector.py (CWE-272)risk surface
•Egress to a private/loopback host — 127.0.0.1 · AntonOsika-gpt-engineer-a90fcd5/scripts/test_api.py (CWE-918)risk surface
⚠LLM07System Prompt Leakagemedium
Secrets, internal hosts or proprietary logic exposed in shipped prompts.
•Internal host / private infrastructure reference — shipped content references a private IP range or internal-only host · AntonOsika-gpt-engineer-a90fcd5/tests/core/improve_function_test_cases/wheaties_example_code (CWE-200)risk surface
•Low-confidence secret match — 1 possible: generic-api-key · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/applications/cli/collect.py (CWE-798)risk surface
•Low-confidence secret match — 1 possible: generic-api-key · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/core/token_usage.py (CWE-798)risk surface
⚠LLM10Unbounded Consumptionmedium
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.
•Potentially unbounded loop — an infinite loop (while True / while(1) / for(;;)) may cause runaway consumption · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/applications/cli/main.py (CWE-835)risk surface
⚠LLM02Sensitive Information Disclosurelow
Secrets, credentials or PII shipped inside the artifact.
•Low-confidence secret match — 1 possible: generic-api-key · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/applications/cli/collect.py (CWE-798)risk surface
•Low-confidence secret match — 1 possible: generic-api-key · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/core/token_usage.py (CWE-798)risk surface
§LLM09MisinformationGovernance
Artifacts designed to produce false/deceptive output.
Detectable only by runtime behavioral evaluation; addressed via responsible-use attestation.
✓LLM01Prompt InjectionPassed
✓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.
✓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
⚠ML06AI Supply Chaincritical
Compromised PyPI/npm packages, typosquats, unsafe serialized models.
•Dependency manifest — 1 pip requirements declared · AntonOsika-gpt-engineer-a90fcd5/projects/example-improve/requirements.txtrisk surface
•Vulnerable dependencies — 184 known vulnerabilities in: aiohttp@3.9.5, black@23.3.0, bleach@6.1.0, filelock@3.13.4, h11@0.14.0, idna@3.7, jinja2@3.1.3, jupyter-core@5.7.2 (CWE-1395)known CVE · -25 pts
⚠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 / · AntonOsika-gpt-engineer-a90fcd5/docker/Dockerfile (CWE-78)risk surface
•Suspicious code patterns — world-writable chmod 777 · AntonOsika-gpt-engineer-a90fcd5/docker/entrypoint.sh (CWE-732)risk surface
•Suspicious code patterns — OS command execution · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/applications/cli/file_selector.py (CWE-78)risk surface
•Suspicious code patterns — dynamic code execution · AntonOsika-gpt-engineer-a90fcd5/gpt_engineer/core/project_config.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.
✓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 (9) · hygiene / uncategorized
•Unrecognized file type — '.dockerignore' is not on the allowlist · AntonOsika-gpt-engineer-a90fcd5/.dockerignorerisk surface
•Unrecognized file type — '.template' is not on the allowlist · AntonOsika-gpt-engineer-a90fcd5/.env.templaterisk surface
•Unrecognized file type — '.?' is not on the allowlist · AntonOsika-gpt-engineer-a90fcd5/.github/CODEOWNERSrisk surface
•Unrecognized file type — '.gitignore' is not on the allowlist · AntonOsika-gpt-engineer-a90fcd5/.gitignorerisk surface
•Unrecognized file type — '.in' is not on the allowlist · AntonOsika-gpt-engineer-a90fcd5/MANIFEST.inrisk surface
•Unrecognized file type — '.cff' is not on the allowlist · AntonOsika-gpt-engineer-a90fcd5/citation.cffrisk surface
•Disallowed file type — '.bat' executables are not permitted · AntonOsika-gpt-engineer-a90fcd5/docs/make.bat (CWE-434)risk surface
•Suspicious network references — raw IP URL (1 URLs) · AntonOsika-gpt-engineer-a90fcd5/scripts/test_api.pyrisk surface
•Unrecognized file type — '.ini' is not on the allowlist · AntonOsika-gpt-engineer-a90fcd5/tox.inirisk surface
✔ verified source · pinned AntonOsika-gpt-engineer-a90fcd5
Check against a policy

The same gate an agent runs before installing (POST /api/v1/trust/gpt-engineer-code-generator/check). Click a policy:

Consume GPT Engineer 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/gpt-engineer-code-generator

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

# CLI
npx ai-supply add gpt-engineer-code-generator

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

# MCP tool
install_listing({ "slug": "gpt-engineer-code-generator" })
OpenAPI spec →
vlatest
! Security: Review · 751mo ago

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

Sign in and install this listing to leave a review.

More from @ai-supply

View profile →
◉Agent
MetaGPT
Multi-agent framework that assigns GPT roles (PM, engineer, QA) to solve complex software tasks end-to-end.
↓ 1.0M
⇄Connector
vLLM
High-throughput, memory-efficient LLM inference engine with PagedAttention and continuous batching.
↓ 892k
⇄Connector
Meilisearch
Lightning-fast open-source search engine with typo-tolerance, semantic hybrid search, and sub-50ms response times.
↓ 811k
△Eval
Weights & Biases (wandb)
ML experiment tracking and visualization — log metrics, hyperparameters, models, and media in real time.
↓ 784k
ai-supply.store

無料でセキュリティ監査済みのAI機能。スキル、MCP、プラグイン、agent、データセットまで、一つひとつをスコアリングし鮮度も追跡。人にもagentにも使えるように設計されています。

api · v3.1status · all green
お問い合わせ
support@ai-supply.storesecurity@ai-supply.store
カタログ
  • 探す
  • カテゴリ
  • ランキング
  • ベンチマーク
  • セキュリティ
  • Scan a repo
コミュニティ
  • コミュニティ
  • FAQ
エージェント向け
  • クイックスタート (60s)
  • エージェントを認可
  • Agent API
  • OpenAPI 仕様
ビルダー向け
  • 公開する
  • ダッシュボード
アカウント
  • アカウント作成
  • サインイン
  • 設定
法的情報
  • 利用規約
  • パブリッシャー契約
  • 利用規定
  • プライバシーポリシー