'jailbreak detection' 검색 결과

Add safety checks to LLM applications with NeMo Guardrails. This skill guides input and output validation, detection of attempts to bypass safety rules, personal information masking, and checks for unsupported or inaccurate answers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Detect attempts to bypass an AI app's safety rules
• Mask personal information before processing
• Add fact-checking to generated answers

Configure safety checks for LLM applications with NeMo Guardrails. Covers attempts to bypass safety rules, input and output validation, masking personal information, and checking factual claims through programmable rules and integrations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Detecting instructions that try to bypass safety rules
• Masking personal information before processing
• Adding factual checks to generated answers

Detects weak reverse engineering and tampering protections in mobile apps (Android/iOS). Trigger on: root detection bypass, jailbreak detection bypass, Frida detection, debugger detection, anti-debugging, ptrace, sysctl, emulator detection, code obfuscation absent, debug symbols present, get-task-allow, ProGuard disabled, R8 disabled, string encryption, integrity check, file tampering, repackaging, dynamic instrumentation, runtime hook, Magisk hide, Magisk, frida-server, objection bypass, signing verification, apk resign. Covers MASVS-RESILIENCE-1/2/3/4.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use Meta's Prompt Guard to detect malicious instructions in user prompts and external data. This skill guides input filtering, batch checks for retrieved documents, detection threshold adjustments, and splitting long text for inspection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Detecting attempts to override an LLM's instructions
• Checking API responses for embedded malicious instructions
• Batch screening documents retrieved for RAG

Audit iOS and Android mobile applications against OWASP MASVS / MASTG — insecure storage, weak crypto, certificate pinning, deeplinks, IPC, jailbreak/root detection, reverse-engineering resistance. Use when the user mentions 'mobile security,' 'iOS security,' 'Android security,' 'mobile audit,' 'mobile pentest,' 'MASVS,' 'MASTG,' 'certificate pinning,' 'jailbreak detection,' 'root detection,' 'deeplink,' 'URL scheme,' 'app transport security,' 'keychain,' 'keystore,' 'mobile reverse engineering,' or has a mobile app to review.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement comprehensive safety guardrails for LLM applications including content moderation (OpenAI Moderation API), jailbreak prevention, prompt injection defense, PII detection, topic guardrails, and output validation. Essential for production AI applications handling user-generated content. Use when ", guardrails, content-moderation, prompt-injection, jailbreak-prevention, pii-detection, nemo-guardrails, openai-moderation, llama-guard, safety" mentioned.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Execute dynamic instrumentation utilizing Frida to inject custom JavaScript into running iOS applications (IPAs) on jailbroken devices. Hook native functions, bypass SSL Pinning, bypass Jailbreak Detection, and manipulate in-memory data at runtime.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Framework de segurança em runtime da NVIDIA para aplicações LLM. Com detecção de jailbreak, validação de entrada/saída, verificação de fatos, detecção de alucinações, filtragem de PII, detecção de toxicidade. Usa DSL Colang 2.0 para rails programáveis. Pronto para produção, executa em GPU T4.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Assess security risks in AI systems by scanning prompts for known attack patterns and scoring data exposure, poisoning, and tool abuse risks. Map findings to MITRE ATLAS, an AI threat framework, and identify protective controls.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Scan application prompts for injection and jailbreak patterns
• Review malicious instructions in retrieved documents
• Assess training data exposure and poisoning risks

Guides security testing of Android and iOS apps through file inspection and observation while the app runs. Covers network traffic, stored secrets, external app interfaces, authentication, and backend APIs, with tool examples and a testing checklist.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Inspecting APK or IPA files for endpoints and embedded secrets
• Observing app behavior and traffic with Frida
• Reviewing deep links and externally accessible components

Expert guide for defending AI applications against prompt injection, jailbreak attacks, indirect injection via tool outputs, and data exfiltration through tool calls — input sanitization, output filtering, canary token detection, and layered defense architecture / Panduan ahli pertahanan aplikasi AI terhadap prompt injection, serangan jailbreak, injeksi tidak langsung via output tool, dan eksfiltrasi data melalui tool calls — sanitasi input, filtering output, deteksi canary token, dan arsitektur pertahanan berlapis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Comprehensive LLM security testing: bias detection, data leakage, prompt injection, jailbreak, alignment testing, adversarial prompts

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Test iOS apps while they run using Objection and Frida, tools for inspecting and changing runtime behavior. Examine stored credentials, files, memory, and authentication calls, and evaluate client-side protections during authorized security assessments.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check stored iOS app data for sensitive information
• Inspect HTTPS traffic during authorized testing
• Observe authentication behavior without source code

Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Secure storage, certificate pinning, biometric auth, jailbreak detection, code obfuscation, network security, screenshot prevention for React Native

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detects authentication and biometric bypass vulnerabilities in mobile apps (Android/iOS). Trigger on: BiometricPrompt, LocalAuthentication, LAContext, evaluatePolicy, CryptoObject, Android Keystore, Secure Enclave, kSecAccessControlBiometryCurrentSet, userAuthenticationValidityDurationSeconds, confirmCredentials, biometric fallback, PIN bypass, passive authentication, enrolled biometrics detection, Frida hook auth, jailbreak bypass, TouchID, FaceID, fingerprint. Covers MASVS-AUTH-1/2/3.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Authorized testing of LLM applications, agents, chatbots, RAG systems, guardrails, and tool-using model workflows. Use for LLM mode selection, jailbreak and prompt-injection assessment, guardrail bypass review, tool misuse, tool or system prompt disclosure, data exfiltration paths, model refusal/stop detection, bypass hypotheses, and hardening guidance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, co...

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Mobile (Android + iOS) application penetration testing methodology. Covers static analysis (apktool/jadx for Android, class-dump/Hopper/IDA for iOS), dynamic instrumentation with Frida and Objection, SSL pinning bypass strategies, root/jailbreak detection bypass, deep-link / URL-scheme abuse, exported component attacks (Android activities, services, providers, receivers; iOS XPC, URL schemes, universal links), insecure data storage (SharedPrefs, KeyStore misuse, NSUserDefaults, Keychain ACL bypass), IPC / Intent redirection, WebView vulnerabilities (JavaScriptInterface, file:// access), Firebase/AWS/Azure misconfiguration leakage, mobile API testing, biometric/Face ID/Touch ID bypass, app-cloning and runtime patching, and mobile malware/RAT analysis primitives. Use for mobile pentest, bug bounty mobile triage, or app-store reconnaissance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.