Systematic methodology for discovering novel vulnerabilities through manual code auditing, fuzzing, reverse engineering, and creative attack chaining during authorized security assessments.
Systematic methodology for safely confirming and documenting exploited vulnerabilities with reproducible proof, ensuring zero false positives before reporting.
Identifying and exploiting insecure file upload functionality to achieve remote code execution, stored XSS, path traversal, and denial of service during authorized penetration tests.
Identifying and exploiting dangling DNS records pointing to unclaimed cloud services, enabling subdomain takeover for phishing, cookie stealing, and authentication bypass during authorized penetration tests.
Testing WordPress, Drupal, Joomla, and other CMS platforms for known vulnerabilities, plugin/theme exploits, misconfigured permissions, and CMS-specific attack vectors during authorized penetration tests.
Offensive email security assessment covering SMTP open relay, SPF/DKIM/DMARC bypass, email header injection, and email-based attack vectors during authorized penetration tests.
Performs firmware image extraction and analysis using binwalk to identify embedded filesystems, compressed archives, bootloaders, kernel images, and cryptographic material. Covers entropy analysis for detecting encrypted or compressed regions, recursive extraction of nested archives, SquashFS/CramFS/JFFS2 filesystem mounting, and string analysis for credential and configuration discovery. Activates for requests involving firmware reverse engineering, IoT device analysis, embedded system security assessment, or router/camera firmware extraction.
Detects prompt injection attacks targeting LLM-based applications using a multi-layered defense combining regex pattern matching for known attack signatures, heuristic scoring for structural anomalies, and transformer-based classification with DeBERTa models. The detector analyzes user inputs before they reach the LLM, flagging direct injections (system prompt overrides, role-play escapes, instruction hijacking) and indirect injections (encoded payloads, multi-language obfuscation, delimiter-based escapes). Based on the OWASP LLM Top 10 (LLM01:2025 Prompt Injection) and Simon Willison's prompt injection taxonomy. Activates for requests involving prompt injection detection, LLM input sanitization, AI security scanning, or prompt attack classification.