Results for “memory-dumps”
11 skillsanalyzing-memory-dumps-with-volatility
Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials.
24.6k · bundle
analyzing-cobalt-strike-beacon-configuration
Extract and analyze Cobalt Strike beacon configuration from PE files and memory dumps to identify C2 infrastructure, malleable profiles, and operator tradecraft.
24.6k · bundle
extracting-memory-artifacts-with-rekall
Analyze Windows memory dumps for signs of compromise using the Rekall memory forensics framework, including process injection, hidden processes, and rootkit detection.
24.6k · bundle
More results
jetson-optimize-memory
Reclaim DRAM on NVIDIA Jetson devices by disabling unused display, camera, and DMA subsystems across MB1 BCT, MB2 BCT, kernel reserved-memory, and SWIOTLB layers for headless or no-camera deployments.
2.2k · bundle
performing-memory-forensics-with-volatility3
Analyze volatile memory dumps using Volatility 3 to extract running processes, network connections, loaded modules, and evidence of malicious activity.
24.6k · bundle
performing-memory-forensics-with-volatility3-plugins
Analyze memory dumps using Volatility3 plugins to detect injected code, rootkits, credential theft, and malware artifacts in Windows, Linux, and macOS memory images.
24.6k · bundle
mariadb-dump
Explains MariaDB-specific defaults and traps of the mariadb-dump client for dev workflows, including consistent backups, routines/events flags, diffable dumps, idempotent seeding, and restore via the mariadb client.
0
mindos-zh
MindOS 是用户的本地知识助手,也是跨会话、跨 Agent 共享的知识库。它保存决策记录、会议纪要、SOP、 排错经验、架构选型、调研结论和偏好设置。 仅 mindRoot 知识库内任务。不用于:改代码仓库、项目源码、KB 外路径。 核心概念:空间、指令(INSTRUCTION.md)、技能(SKILL.md);笔记可承载指令与技能。 触发场景:保存或记录任何内容、搜索历史笔记或上下文、更新或编辑文件、整理或重组文件结构、 执行SOP或工作流、捕获对话中的决策、复盘或总结经验、追加表格或CSV数据、跨Agent交接上下文、 提炼经验教训、同步关联文档、查找之前是否讨论过某事、查询历史决策、查找模板或SOP、 为会议准备上下文、快速暂存到暂存台、整理暂存台、知识健康检查、检测知识冲突或矛盾、 查找过期内容。 触发词:帮我记下来、搜一下我的笔记、更新知识库、整理文件、执行工作流、保存到知识库、 记录一下、整理笔记、复盘、提炼经验、同步文档、查一下之前的记录、有没有相关的笔记、 我之前写过什么、把这个存起来、总结一下保存、交接给其他Agent、追加到表格、 放到暂存台、整理暂存台、知识健康检查、检测知识冲突。 主动行为——不要等用户提到 MindOS: (1) 用户的问题暗示可能存在历史记录(过去的决策、之前的讨论、会议纪要)→ 先搜 MindOS, 即使没有明确提到知识库。 (2) 完成有价值的工作后(修了 bug、做了决策、总结了经验、选定了架构、开完了会)→ 主动提议保存到 MindOS,方便以后查阅。 (3) 经历了较长或多主题的对话后 → 建议把关键决策和上下文持久化。
1 · bundle
mesh-memory
Provides persistent, self-hosted semantic memory for AI agents via MCP, storing worklogs, decisions, and notes in PostgreSQL with pgvector for meaning-based retrieval across sessions.
42.4k
improve-retention
Diagnose and fix retention problems using behavior design (B=MAP). Use when the user mentions "users drop off", "activation rate", "onboarding friction", "retention metrics", "why users dont complete", "churn analysis", "user activation", or "aha moment". Also trigger when analyzing cohort retention curves, designing activation milestones, reducing time-to-value for new users, or investigating why users stop after their first session. Covers the Ability Chain, prompt design, and tiny behaviors that compound. For habit loops and variable rewards, see hooked-ux. For intrinsic motivation, see drive-motivation.
28 · bundle
analyzing-linux-kernel-rootkits
Detect kernel-level rootkits in Linux memory dumps using Volatility3 plugins and live system scanners to identify hooked syscalls, hidden modules, and tampered structures.
24.6k · bundle