{ "report": { "version": "1.0", "server": { "slug": "awesome-github-repositories", "name": "Awesome-GitHub-Repositories", "github_url": "https://github.com/avinash201199/awesome-github-repositories", "scan_id": "944d8e12-3060-48a4-a622-ff99ae540798" }, "framework": { "id": "eu_ai_act", "name": "EU AI Act", "version": "2024/1689", "last_updated": "2026-04-23", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1689" }, "assessment": { "assessed_at": "2026-05-10T06:20:25.849Z", "rules_version": "2026-04-23", "sentinel_version": "0.4.0", "coverage_band": "low", "coverage_ratio": 0.4, "techniques_run": [ "ast-taint", "capability-graph", "entropy", "linguistic-scoring", "schema-inference" ] }, "controls": [ { "control_id": "Art.9", "control_name": "Risk Management System", "control_description": "High-risk AI providers must establish, implement, and maintain a risk management system covering the entire lifecycle, including analysis of reasonably foreseeable misuse and supply-chain risk.", "source_url": "https://artificialintelligenceact.eu/article/9/", "status": "met", "evidence": [], "rationale": "22 assessor rule(s) evaluated this control; no findings observed.", "required_mitigations": [], "assessor_rule_ids": [ "D1", "D2", "D3", "D4", "D5", "D6", "D7", "K9", "K10", "K11", "L1", "L2", "L3", "L5", "L6", "L7", "L8", "L10", "L12", "L13", "Q4", "Q13" ] }, { "control_id": "Art.12", "control_name": "Record-Keeping", "control_description": "High-risk AI systems must automatically record events ('logs') over the system lifetime to ensure traceability of the system's functioning appropriate for the intended purpose.", "source_url": "https://artificialintelligenceact.eu/article/12/", "status": "met", "evidence": [], "rationale": "5 assessor rule(s) evaluated this control; no findings observed.", "required_mitigations": [], "assessor_rule_ids": [ "K1", "K2", "K3", "K20", "E3" ] }, { "control_id": "Art.13", "control_name": "Transparency & Provision of Information to Deployers", "control_description": "High-risk AI systems must be sufficiently transparent to enable deployers to interpret the system's output appropriately, including capabilities, limitations, and the conditions of intended use.", "source_url": "https://artificialintelligenceact.eu/article/13/", "status": "unmet", "evidence": [ { "finding_id": "58f30e9a-a67a-416c-8a7f-97c6ac5a0ef3", "rule_id": "F5", "severity": "critical", "evidence_summary": "SOURCE: external-content at initialize.server_name — The MCP client surfaces the server name verbatim in its approval dialog, and the LLM ingests the server name alongside the tool descriptions. A nam", "confidence": 0.9 } ], "rationale": "14 assessor rule(s) evaluated this control; 1 finding(s) observed (1 critical); at least one finding is at or above the high threshold (status: unmet).", "required_mitigations": [ "If you own the server and are NOT affiliated with the vendor whose namespace it contains, rename the server to remove the vendor token. Choose a name that makes your actual publisher identity clear. If you ARE a vendor-approved partner and intentionally use the vendor's namespace, request inclusion in the rule's OFFICIAL_NAMESPACES.verified_github_orgs list by publishing the server under a vendor-sanctioned GitHub organisation. Users deciding whether to approve the server should check the repository owner against the vendor's published list of approved partners before granting trust." ], "assessor_rule_ids": [ "A2", "A4", "A6", "A8", "F2", "F5", "G6", "I1", "I2", "I5", "I16", "K12", "K13", "L15" ] }, { "control_id": "Art.14", "control_name": "Human Oversight", "control_description": "High-risk AI systems must be designed so that they can be effectively overseen by natural persons during use. Covers the ability to fully understand, monitor, and intervene in the system's operation.", "source_url": "https://artificialintelligenceact.eu/article/14/", "status": "met", "evidence": [], "rationale": "13 assessor rule(s) evaluated this control; no findings observed.", "required_mitigations": [], "assessor_rule_ids": [ "K4", "K5", "I12", "M5", "M6", "Q15", "H3", "F1", "F6", "J1", "K14", "K15", "Q10" ] }, { "control_id": "Art.15", "control_name": "Accuracy, Robustness, and Cybersecurity", "control_description": "High-risk AI systems must achieve appropriate levels of accuracy, robustness, and cybersecurity throughout their lifecycle. Covers resilience against errors, faults, and adversarial manipulation.", "source_url": "https://artificialintelligenceact.eu/article/15/", "status": "met", "evidence": [], "rationale": "111 assessor rule(s) evaluated this control; no findings observed.", "required_mitigations": [], "assessor_rule_ids": [ "A1", "A3", "A5", "A7", "A9", "B1", "B2", "B3", "B4", "B5", "B6", "B7", "C1", "C2", "C3", "C4", "C5", "C6", "C7", "C8", "C9", "C10", "C11", "C12", "C13", "C14", "C15", "C16", "E1", "E2", "E4", "F3", "F4", "F7", "G1", "G2", "G3", "G4", "G5", "G7", "H1", "H2", "I3", "I4", "I6", "I7", "I8", "I9", "I10", "I11", "I13", "I15", "J2", "J3", "J4", "J5", "J6", "J7", "K6", "K7", "K8", "K16", "K17", "K18", "K19", "L4", "L9", "L11", "L14", "M1", "M2", "M4", "M7", "M8", "M9", "N1", "N2", "N3", "N4", "N5", "N6", "N7", "N8", "N9", "N10", "N11", "N12", "N13", "N14", "N15", "O4", "O5", "O6", "O8", "O9", "O10", "P1", "P2", "P3", "P4", "P5", "P6", "P7", "P8", "P9", "P10", "Q3", "Q6", "Q7", "Q10", "Q15" ] } ], "summary": { "total_controls": 5, "met": 4, "unmet": 1, "partial": 0, "not_applicable": 0, "overall_status": "non_compliant" }, "kill_chains": [], "executive_summary": "Assessment of Awesome-GitHub-Repositories against EU AI Act: overall status non compliant. Of 5 controls, 4 met, 1 unmet, 0 partial, 0 not applicable. 5 control(s) fell within MCP Sentinel's current assessor coverage; remaining control(s) are documented as not_applicable until Phase 6 expands coverage. Unmet controls have findings at or above the framework's mandatory severity threshold and should be remediated before relying on this server in a regulated deployment. All claims are traceable to individual finding rows via finding_id and to the governing rule via rule_id; the enclosing signed envelope commits MCP Sentinel to the exact bytes of this report." }, "attestation": { "algorithm": "HMAC-SHA256", "signature": "GGmcFBTqtnoZdhAmc6mBmACmvYBazxL+3yjMUarMZ8o=", "key_id": "mcp-sentinel-dev", "signed_at": "2026-05-14T09:24:21.770Z", "signer": "mcp-sentinel/v1", "canonicalization": "RFC8785" } }