Skip to content
cccskills
FreePublished on GitHub

detecting-ransomware-precursors-in-network

Develop network monitoring for signs that may precede ransomware encryption. Uses detection rules, linked log events, and threat intelligence to identify suspicious activity and define how alerts should be investigated, prioritized, and escalated.

OriginalShow the original description

Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

Run score Not tested

See how to install

Good for

  • Creating detection rules for activity before ransomware encryption
  • Linking suspicious logins, scans, and file share access
  • Investigating unusual internal network communications
  • Defining alert triage and escalation procedures

Files included (8)

  • SKILL.md14.5 KB
  • assets/template.md1.6 KB
  • LICENSE11.0 KB
  • references/api-reference.md5.2 KB
  • references/standards.md1.7 KB
  • references/workflows.md2.6 KB
  • scripts/agent.py7.2 KB
  • scripts/process.py19.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Assess exposure of Windows secrets protected by DPAPI, the operating system’s data protection service, during authorized security tests. Guide examination and decryption of saved credentials and browser data using available user sessions, credentials, or backup keys.

  • Assessing saved credential exposure in authorized tests
  • Examining collected DPAPI files offline
  • Reviewing protected browser and RDP credentials
mukul975/Anthropic-Cybersecurity-Skills34.9KUpdated Aug 31, 2026

Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.

  • Assessing risky permissions identified in BloodHound
  • Validating account takeover without resetting a password
  • Generating directory change records during security exercises
mukul975/Anthropic-Cybersecurity-Skills34.9KUpdated Aug 31, 2026

Prepare for CMMC Level 2, a cybersecurity certification for defense contractors. Define the systems handling controlled information, review security requirements, calculate the SPRS assessment score, and organize remediation plans and evidence into a readiness report.

  • Define the assessment scope for systems handling controlled information
  • Calculate an SPRS score and prioritize unmet security requirements
  • Prepare security plans, remediation milestones, and assessment evidence
mukul975/Anthropic-Cybersecurity-Skills34.9KUpdated Aug 31, 2026

Create disk images for investigations using dd or dcfldd on Linux. The workflow covers write protection, bit-for-bit copying, hash checks to verify integrity, and documentation of the acquisition process.

  • Preserving a suspect drive before investigation
  • Creating evidence copies of USB devices or memory cards
  • Verifying that a disk image matches its source
mukul975/Anthropic-Cybersecurity-Skills34.9KUpdated Aug 31, 2026

Review Active Directory permissions with ldap3, a Python library for directory queries. Identify excessive access granted to non-administrative accounts, explain potential privilege escalation paths, and produce a JSON report with affected objects and remediation recommendations.

  • Auditing excessive Active Directory permissions
  • Investigating privilege escalation paths from ordinary accounts
  • Reporting affected objects and permission remediation recommendations
mukul975/Anthropic-Cybersecurity-Skills34.9KUpdated Aug 31, 2026

Inspect suspicious Android APK files without running them. Analyze permissions, app components, suspicious code patterns, and network indicators, then produce a JSON risk report to support malware triage and detection rule development.

  • Triage suspicious APK files without running them
  • Inspect dangerous permission combinations and suspicious API calls
  • Extract network indicators for malware detection rules
mukul975/Anthropic-Cybersecurity-Skills34.9KUpdated Aug 31, 2026

See all skills by mukul975

Report a problem with this skill