Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add killvxk/cybersecurity-skills-zh --skill analyzing-malware-behavior-with-cuckoo-sandboxgit clone --depth 1 https://github.com/killvxk/cybersecurity-skills-zhWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/killvxk/cybersecurity-skills-zh/analyzing-malware-behavior-with-cuckoo-sandbox)<a href="https://agentmods.dev/skills/killvxk/cybersecurity-skills-zh/analyzing-malware-behavior-with-cuckoo-sandbox"><img src="https://agentmods.dev/badge/skills/killvxk/cybersecurity-skills-zh/analyzing-malware-behavior-with-cuckoo-sandbox/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/killvxk/cybersecurity-skills-zh/analyzing-malware-behavior-with-cuckoo-sandbox"><img src="https://agentmods.dev/badge/skills/killvxk/cybersecurity-skills-zh/analyzing-malware-behavior-with-cuckoo-sandbox.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00095 | $0.03182 |
| Opus 5 | $0.00048 | $0.01591 |
| Sonnet 5 | $0.00019 | $0.00636 |
| Haiku 4.5 | $0.00010 | $0.00318 |
Grade A, and why
analyzing-malware-behavior-with-cuckoo-sandbox scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -F "[email protected]" -F "timeout=300" -F "machine=win10_x64" \ How it starts
The opening of the file, as written. The whole thing — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
使用 Cuckoo Sandbox 分析恶意软件行为
适用场景
- 可疑样本通过静态分析分类后,需要在受控环境中进行行为观察
- 需要捕获恶意软件执行期间的网络流量、文件投放、注册表修改和 API 调用
- 确定完整的感染链,包括第二阶段载荷下载和持久化机制
- 基于观察到的运行时活动生成行为签名和 YARA 规则
- 对批量恶意软件样本进行自动化分析,要求一致的报告输出
不适用于在配置错误的沙箱中通过网络共享传播的已知勒索软件变种;请先验证网络隔离。
前置条件
- Cuckoo Sandbox 3.x 安装在专用分析服务器上(推荐 Ubuntu 22.04)
- 配置了 Windows 10/11 快照的客户虚拟机(安装 Cuckoo agent,在干净状态下拍取快照)
- VirtualBox、KVM 或 VMware 配置为 Cuckoo 虚拟化后端
- 隔离网络,使用 InetSim 或 FakeNet-NG 模拟互联网服务
- 集成 Suricata 或 Snort,用于分析期间的网络级签名匹配
- 足够的磁盘空间用于 PCAP 捕获和内存转储(推荐最少 500 GB)
工作流程
步骤 1:向 Cuckoo 提交样本
提交恶意软件样本进行自动化分析:
# 通过命令行提交
cuckoo submit /path/to/suspect.exe
# 提交并指定分析超时时间(300 秒)
cuckoo submit --timeout 300 /path/to/suspect.exe
# 提交并指定虚拟机和分析包
cuckoo submit --machine win10_x64 --package exe --timeout 300 /path/to/suspect.exe
# 通过 REST API 提交
curl -F "[email protected]" -F "timeout=300" -F "machine=win10_x64" \
http://localhost:8090/tasks/create/file
# 提交 URL 进行分析
curl -F "url=http://malicious-site.com/payload" -F "timeout=300" \
http://localhost:8090/tasks/create/url
# 检查任务状态
curl http://localhost:8090/tasks/view/1 | jq '.task.status'
步骤 2:实时监控执行过程
跟踪分析进度并观察实时行为:
# 查看 Cuckoo 分析日志
tail -f /opt/cuckoo/log/cuckoo.log
# 监控分析任务状态
cuckoo status
# 访问 Cuckoo Web 界面查看实时截图和进程树
# 导航到 http://localhost:8080/analysis/<task_id>/
执行期间需关注的关键行为事件:
- 进程创建链(父子进程关系)
- 向外部 IP 发起的网络连接尝试
- 在临时目录或系统文件夹中投放文件
- 对 Run 键或服务条目的注册表修改
- 与加密(CryptEncrypt)、注入(WriteProcessMemory)或逃避相关的 API 调用
步骤 3:分析进程活动
检查 Cuckoo 报告中的进程树和 API 调用跟踪:
# 以编程方式解析 Cuckoo JSON 报告
import json
with open("/opt/cuckoo/storage/analyses/1/reports/report.json") as f:
report = json.load(f)
# 进程树分析
for process in report["behavior"]["processes"]:
pid = process["pid"]
ppid = process["ppid"]
name = process["process_name"]
print(f"PID: {pid} PPID: {ppid} Name: {name}")
# 提取可疑 API 调用
for call in process["calls"]:
api = call["api"]
if api in ["CreateRemoteThread", "VirtualAllocEx", "WriteProcessMemory",
"NtCreateThreadEx", "RegSetValueExA", "URLDownloadToFileA"]:
args = {arg["name"]: arg["value"] for arg in call["arguments"]}
print(f" [!] {api}({args})")
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 286 lines · 95 tokens per session scan A 3d5a78c3b769
analyzing-malware-behavior-with-cuckoo-sandbox is a skill published in the GitHub repository killvxk/cybersecurity-skills-zh (44 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 95 tokens to every session and 3,182 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
analyzing-malware-behavior-with-cuckoo-sandbox
Detonate malware samples in Cuckoo Sandbox to observe runtime behavior — process creation, file system and registry changes, network communications, and API calls — and generate behavioral reports for classification and IOC extraction. Use when a sample has passed static triage and needs dynamic/behavioral analysis…
analyzing-malware-behavior-with-cuckoo-sandbox
Executes malware samples in Cuckoo Sandbox to observe runtime behavior including process creation, file system modifications, registry changes, network communications, and API calls. Generates comprehensive behavioral reports for malware classification and IOC extraction. Activates for requests involving dynamic…
analyzing-malware-behavior-with-cuckoo-sandbox
Executes malware samples in Cuckoo Sandbox to observe runtime behavior including process creation, file system modifications, registry changes, network communications, and API calls. Generates comprehensive behavioral reports for malware classification and IOC extraction. Activates for requests involving dynamic…
analyzing-malware-behavior-with-cuckoo-sandbox
Executes malware samples in Cuckoo Sandbox to observe runtime behavior including process creation, file system modifications, registry changes, network communications, and API calls. Generates comprehensive behavioral reports for malware classification and IOC extraction. Activates for requests involving dynamic…
analyzing-malware-behavior-with-cuckoo-sandbox
Executes malware samples in Cuckoo Sandbox to observe runtime behavior including process creation, file system modifications, registry changes, network communications, and API calls. Generates comprehensive behavioral reports for malware classification and IOC extraction. Activates for requests involving dynamic…
analyzing-malware-behavior-with-cuckoo-sandbox
Executes malware samples in Cuckoo Sandbox to observe runtime behavior including process creation, file system modifications, registry changes, network communications, and API calls. Generates comprehensive behavioral reports for malware classification and IOC extraction. Activates for requests involving dynamic…