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detecting-ransomware-precursors-in-networkdetecting ransomware precursors IN network 命令行

Agent Skill

detecting-ransomware-precursors-in-network 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

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请帮我安装这个 Agent Skill:detecting-ransomware-precursors-in-network(detecting ransomware precursors IN network 命令行)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/detecting-ransomware-precursors-in-network
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill detecting-ransomware-precursors-in-network
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill detecting-ransomware-precursors-in-network

简介

用于识别勒索软件部署前的网络准备阶段活动,争取拦截窗口。

  • 适用于 Cobalt Strike 部署到加密前的 17 分钟关键期监控。
  • 关联 C2 通信、凭证收集与敏感文件访问等前置行为。
  • 需建立网络行为基线,区分正常管理与攻击者 staging 活动。
  • detecting-ransomware-precursors-in-network 属于运维和基础设施类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Detecting Ransomware Precursors in Network Traffic

When to Use

  • Building detection rules for pre-ransomware network activity (the average time from Cobalt Strike deployment to encryption is 17 minutes)
  • Monitoring for initial access broker (IAB) indicators that precede ransomware deployment
  • Creating SIEM correlation rules that chain multiple precursor events into high-confidence alerts
  • Tuning network detection systems to distinguish ransomware staging from normal administrative activity
  • Investigating suspicious network patterns that may indicate ransomware operators have established a foothold

Do not use for post-encryption response (see recovering-from-ransomware-attack). This skill focuses on the pre-encryption detection window where containment can prevent data loss.

Prerequisites

  • Network detection platform (Zeek/Bro, Suricata, or Arkime/Moloch) deployed on network TAP or SPAN ports
  • SIEM platform (Splunk, Elastic Security, Microsoft Sentinel, or QRadar) ingesting network logs
  • Threat intelligence feeds covering ransomware IOCs (CISA, abuse.ch, OTX, MISP)
  • Network flow data (NetFlow/IPFIX) from core routers and firewalls
  • DNS query logging from internal resolvers
  • Full packet capture capability for incident investigation

Workflow

Step 1: Identify Ransomware Kill Chain Phases in Network Traffic

Map network-observable indicators to each pre-encryption phase:

Kill Chain PhaseNetwork IndicatorsDetection Source
Initial AccessRDP brute force, VPN credential stuffing, phishing callbackFirewall logs, IDS, proxy logs
C2 EstablishmentCobalt Strike beacons (HTTPS/DNS), Sliver/Brute Ratel callbacksZeek SSL/HTTP logs, DNS logs
Credential HarvestingNTLM relay, Kerberoasting, DCSync trafficZeek Kerberos/NTLM logs, DC logs
ReconnaissanceInternal port scanning, AD enumeration (LDAP/SMB)Zeek conn.log, flow data
Lateral MovementPsExec/WMI/WinRM traffic, RDP pivoting, SMB file copiesZeek SMB/DCE-RPC logs
StagingData aggregation, archive creation, cloud upload prepProxy logs, DNS logs, DLP

Step 2: Deploy Network Detection Rules

Suricata rules for common ransomware precursors:

# Cobalt Strike default HTTPS beacon profile detection
alert tls $HOME_NET any -> $EXTERNAL_NET any (msg:"RANSOMWARE PRECURSOR - Cobalt Strike Default TLS Certificate"; tls.cert_subject; content:"Major Cobalt Strike"; sid:3000001; rev:1;)

# Cobalt Strike DNS beacon
alert dns $HOME_NET any -> any 53 (msg:"RANSOMWARE PRECURSOR - Cobalt Strike DNS Beacon Pattern"; dns.query; pcre:"/^[a-z0-9]{3}\.[a-z]{4,8}\./"; threshold:type both, track by_src, count 50, seconds 60; sid:3000002; rev:1;)

# Mimikatz network signature (DCSync - DRS GetNCChanges)
alert tcp $HOME_NET any -> $HOME_NET 135 (msg:"RANSOMWARE PRECURSOR - Possible DCSync/Mimikatz"; content:"|05 00 0b|"; offset:0; depth:3; content:"|e3 51 4d 2b 4b 47 15 d2|"; sid:3000003; rev:1;)

# Internal network scanning (many connections, few bytes)
alert tcp $HOME_NET any -> $HOME_NET any (msg:"RANSOMWARE PRECURSOR - Internal Port Scan"; flags:S; threshold:type both, track by_src, count 100, seconds 10; sid:3000004; rev:1;)

# PsExec service installation over SMB
alert tcp $HOME_NET any -> $HOME_NET 445 (msg:"RANSOMWARE PRECURSOR - PsExec Service Install"; content:"|ff|SMB"; content:"PSEXESVC"; nocase; sid:3000005; rev:1;)

# RDP brute force from internal host (lateral movement)
alert tcp $HOME_NET any -> $HOME_NET 3389 (msg:"RANSOMWARE PRECURSOR - Internal RDP Brute Force"; flow:to_server,established; threshold:type both, track by_src, count 20, seconds 60; sid:3000006; rev:1;)

# Large SMB file transfer (data staging)
alert tcp $HOME_NET any -> $HOME_NET 445 (msg:"RANSOMWARE PRECURSOR - Large SMB Transfer Possible Staging"; flow:to_server,established; dsize:>60000; threshold:type both, track by_src, count 100, seconds 300; sid:3000007; rev:1;)

Zeek scripts for behavioral detection:

# detect_ransomware_precursors.zeek
# Detect high volume of failed SMB connections (credential testing)

@load base/protocols/smb

module RansomwarePrecursor;

export {
    redef enum Notice::Type += {
        SMB_Brute_Force,
        Suspicious_Internal_Scan,
        Excessive_DNS_Queries,
        SMB_Admin_Share_Access,
    };

    const smb_fail_threshold = 10 &redef;
    const scan_threshold = 50 &redef;
    const dns_query_threshold = 200 &redef;
}

global smb_fail_count: table[addr] of count &default=0 &create_expire=5min;
global conn_count: table[addr] of set[addr] &create_expire=1min;

event smb2_message(c: connection, hdr: SMB2::Header, is_orig: bool) {
    if (hdr$status != 0) {
        ++smb_fail_count[c$id$orig_h];
        if (smb_fail_count[c$id$orig_h] >= smb_fail_threshold) {
            NOTICE([$note=SMB_Brute_Force,
                    $msg=fmt("Host %s has %d failed SMB attempts", c$id$orig_h, smb_fail_count[c$id$orig_h]),
                    $src=c$id$orig_h,
                    $identifier=cat(c$id$orig_h)]);
        }
    }
}

event new_connection(c: connection) {
    if (c$id$orig_h in Site::local_nets && c$id$resp_h in Site::local_nets) {
        if (c$id$orig_h !in conn_count)
            conn_count[c$id$orig_h] = set();
        add conn_count[c$id$orig_h][c$id$resp_h];
        if (|conn_count[c$id$orig_h]| >= scan_threshold) {
            NOTICE([$note=Suspicious_Internal_Scan,
                    $msg=fmt("Host %s connected to %d internal hosts in 1 min", c$id$orig_h, |conn_count[c$id$orig_h]|),
                    $src=c$id$orig_h,
                    $identifier=cat(c$id$orig_h)]);
        }
    }
}

Step 3: Create SIEM Correlation Rules

Splunk correlation for ransomware precursor chain:

| tstats count FROM datamodel=Network_Traffic
  WHERE earliest=-24h All_Traffic.dest_port IN (445, 135, 139, 3389, 5985, 5986)
    AND All_Traffic.src_ip IN 10.0.0.0/8
    AND All_Traffic.dest_ip IN 10.0.0.0/8
  BY All_Traffic.src_ip, All_Traffic.dest_port, _time span=1h
| stats dc(All_Traffic.dest_port) as port_count,
        values(All_Traffic.dest_port) as ports,
        count as total_conns
  BY All_Traffic.src_ip
| where port_count >= 3 AND total_conns > 50
| rename All_Traffic.src_ip as src_ip
| lookup threat_intel_ioc ip as src_ip OUTPUT threat_type
| eval risk_score = case(
    port_count >= 5 AND total_conns > 200, "CRITICAL",
    port_count >= 3 AND total_conns > 50, "HIGH",
    1=1, "MEDIUM")
| table src_ip, ports, port_count, total_conns, risk_score, threat_type

Microsoft Sentinel KQL - Ransomware precursor correlation:

let timeframe = 24h;
let RDPBruteForce = SecurityEvent
| where TimeGenerated > ago(timeframe)
| where EventID == 4625
| where LogonType == 10
| summarize FailedRDP = count() by TargetAccount, IpAddress, bin(TimeGenerated, 1h)
| where FailedRDP > 10;
let SuspiciousSMB = SecurityEvent
| where TimeGenerated > ago(timeframe)
| where EventID == 5145
| where ShareName has "ADMIN$" or ShareName has "C$" or ShareName has "IPC$"
| summarize AdminShareAccess = count() by SubjectUserName, IpAddress, bin(TimeGenerated, 1h)
| where AdminShareAccess > 5;
let ServiceInstalls = SecurityEvent
| where TimeGenerated > ago(timeframe)
| where EventID == 7045
| where ServiceName has_any ("PSEXESVC", "meterpreter", "beacon");
RDPBruteForce
| join kind=inner SuspiciousSMB on IpAddress
| project TimeGenerated, IpAddress, TargetAccount, FailedRDP, SubjectUserName, AdminShareAccess
| extend AlertTitle = "Ransomware Precursor: RDP Brute Force + Admin Share Access"

Step 4: Integrate Threat Intelligence

Configure automated IOC feeds for known ransomware infrastructure:

# Download and update ransomware C2 blocklists
# abuse.ch Feodo Tracker (Cobalt Strike, TrickBot, BazarLoader C2s)
curl -s https://feodotracker.abuse.ch/downloads/ipblocklist.csv | \
  grep -v "^#" | cut -d, -f2 > /opt/threat-intel/feodo_ips.txt

# abuse.ch URLhaus (malware distribution URLs)
curl -s https://urlhaus.abuse.ch/downloads/csv_recent/ | \
  grep -v "^#" | cut -d, -f3 > /opt/threat-intel/urlhaus_urls.txt

# abuse.ch ThreatFox (ransomware IOCs)
curl -s https://threatfox.abuse.ch/export/csv/recent/ | \
  grep -i "ransomware" | cut -d, -f3 > /opt/threat-intel/ransomware_iocs.txt

# CISA Known Exploited Vulnerabilities (initial access vectors)
curl -s https://www.cisa.gov/sites/default/files/feeds/known_exploited_vulnerabilities.json | \
  python3 -c "import json,sys; data=json.load(sys.stdin); [print(v['cveID'],v['vendorProject'],v['product']) for v in data['vulnerabilities'] if 'ransomware' in v.get('knownRansomwareCampaignUse','').lower()]"

Step 5: Establish Alert Triage and Escalation

Define triage procedures based on precursor confidence level:

Alert TypeConfidenceResponse TimeAction
Confirmed Cobalt Strike beaconHigh15 minutesIsolate host immediately, trigger IR
DCSync/Kerberoasting from non-DCHigh15 minutesDisable account, isolate host, trigger IR
Internal port scan + admin share accessMedium-High30 minutesInvestigate source host, check EDR telemetry
RDP brute force from internal hostMedium1 hourVerify if legitimate admin activity, check host
Unusual DNS query volumeLow-Medium4 hoursCheck for DNS tunneling, correlate with other alerts

Key Concepts

TermDefinition
Ransomware PrecursorNetwork activity that precedes ransomware encryption, including C2 communication, lateral movement, and data staging
Dwell TimeTime between initial compromise and ransomware deployment, averaging 21 days but sometimes as short as 17 minutes
Initial Access Broker (IAB)Threat actors who sell compromised network access to ransomware operators on dark web markets
BeaconingPeriodic C2 callbacks from implants (Cobalt Strike, Sliver) that can be detected by analyzing connection timing patterns
KerberoastingCredential harvesting technique requesting Kerberos service tickets for offline cracking, detectable via unusual TGS-REQ patterns
DCSyncTechnique using Directory Replication Service to extract password hashes from domain controllers, critical ransomware precursor

Tools & Systems

  • Zeek (formerly Bro): Network analysis framework generating structured logs for SMB, Kerberos, DNS, HTTP, and TLS connections
  • Suricata: High-performance IDS/IPS with protocol analysis and multi-threading support for ransomware signature detection
  • Arkime (formerly Moloch): Full packet capture and search platform for deep forensic investigation of network events
  • RITA (Real Intelligence Threat Analytics): Open-source tool for detecting beaconing, DNS tunneling, and long connections in Zeek logs
  • AC-Hunter: Network threat hunting platform from Active Countermeasures for beacon detection and C2 identification

Common Scenarios

Scenario: Detecting LockBit Precursors in a Manufacturing Network

Context: A manufacturing company's SOC receives an alert for unusual SMB traffic from a workstation (10.1.5.42) in the engineering department. The workstation connected to 47 internal hosts on port 445 within 5 minutes at 2:00 AM.

Approach:

  1. Zeek conn.log analysis shows 10.1.5.42 initiated connections to 47 unique internal IPs on port 445, 135, and 3389 between 01:55-02:05
  2. Zeek ssl.log reveals an outbound HTTPS connection to 185.x.x.x every 60 seconds with consistent 48-byte payloads (Cobalt Strike beacon pattern)
  3. RITA beacon analysis confirms high beacon score (0.96) for the external IP with 60-second jitter
  4. Zeek kerberos.log shows TGS-REQ for multiple SPN accounts from 10.1.5.42 (Kerberoasting)
  5. SMB tree_connect events show access to ADMIN$ shares on 12 hosts (lateral movement staging)
  6. Containment: Host isolated, credentials for engineering user reset, blocking rule for C2 IP deployed
  7. Full IR initiated before ransomware deployment could begin

Pitfalls:

  • Dismissing internal port scans as vulnerability scanner activity without verifying the source is an authorized scanner
  • Not correlating individual low-severity alerts (DNS anomaly + SMB access + failed logins) into a high-severity chain
  • Setting detection thresholds too high to avoid false positives, missing low-and-slow reconnaissance
  • Ignoring encrypted traffic analysis (JA3/JA4 fingerprinting) that can identify Cobalt Strike even in TLS tunnels

Output Format

## Ransomware Precursor Detection Alert

**Alert ID**: [SIEM-generated ID]
**Detection Time**: [Timestamp]
**Source Host**: [IP / Hostname]
**Confidence**: [High / Medium / Low]
**Kill Chain Phase**: [Initial Access / C2 / Credential Harvest / Recon / Lateral Movement / Staging]

### Indicators Detected
| Indicator | Source | Detail | MITRE ATT&CK |
|-----------|--------|--------|--------------|
| [Type] | [Zeek/Suricata/SIEM] | [Description] | [T-ID] |

### Correlation Chain
1. [Timestamp] - [Event 1]
2. [Timestamp] - [Event 2]
3. [Timestamp] - [Event 3]

### Recommended Actions
- [ ] Isolate source host from network
- [ ] Check EDR telemetry for host-based indicators
- [ ] Reset credentials for affected user accounts
- [ ] Block identified C2 infrastructure
- [ ] Escalate to incident response team

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平台分布

Codex

34.22%
按下载量换算25

Claude

28.79%
按下载量换算21

Cursor

20.24%
按下载量换算15

Gemini CLI

10.32%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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