Results for “toxicity”

Detect and exploit JavaScript prototype pollution vulnerabilities on both client-side and server-side applications to achieve XSS, RCE, and authentication bypass through property injection.

Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials.

Scan Model Context Protocol servers and tool metadata for poisoning, SSRF, and unauthenticated exposure.

Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.

Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.

Tests web applications for Cross-Site Scripting (XSS) vulnerabilities by injecting JavaScript payloads into reflected, stored, and DOM-based contexts to demonstrate client-side code execution, session hijacking, and user impersonation.

Detect abuse of legitimate Windows binaries (LOLBins) like certutil, regsvr32, mshta, and rundll32 using process telemetry, Sigma rules, and parent-child process analysis.

Hunt for adversary abuse of Living Off the Land Binaries (LOLBins) by analyzing endpoint process creation logs for suspicious execution patterns of legitimate Windows system binaries used for malicious purposes.

Detect and exploit DOM-based XSS vulnerabilities by auditing JavaScript for tainted data flow from controllable sources to dangerous sinks, with payloads and bypass techniques for client-side testing.