Overview attacks on DNS¶
Attack tree (DNS)¶
This attack tree outlines the methodologies for compromising DNS integrity, from classic cache poisoning and sophisticated DDoS amplification to AI-augmented phishing automation and the looming threat of cryptographic harvesting in the post-quantum era.
1. Exploit Protocol Weaknesses [OR]
1.1 Cache Poisoning [AND]
1.1.1 Exploit weak TXID entropy in DoH/DoT/DoQ resolvers [OR]
1.1.1.1 Birthday attack on 16-bit TXID space
1.1.1.2 Timing attacks on resolver response handling
1.1.1.3 Fragment-based poisoning attacks
1.1.2 Side-channel attacks on encrypted DNS [OR]
1.1.2.1 TLS padding oracle attacks on DoT
1.1.2.2 QUIC protocol timing analysis on DoQ
1.1.2.3 HTTP/2 stream correlation attacks on DoH
1.1.3 DNSSEC Exploitation [OR]
1.1.3.1 NSEC/NSEC3 walking for zone enumeration
1.1.3.2 RRSIG timing attacks for key recovery
1.1.3.3 Algorithm downgrade attacks (ECDSA to RSA)
Prerequisite: AND (Attacker can intercept traffic AND resolver lacks full DNSSEC validation)
1.2 DDoS Amplification [OR]
1.2.1 Abuse misconfigured encrypted DNS resolvers [OR]
1.2.1.1 DoQ reflection with large TXT records
1.2.1.2 DoH POST request amplification
1.2.1.3 DoT session resumption attacks
1.2.2 DNSSEC-based amplification [OR]
1.2.2.1 NSEC3 response amplification
1.2.2.2 Large RRSIG reflection attacks
1.2.2.3 DNAME chain exploitation
Prerequisite: AND (Open resolver available AND vulnerable payload size > 1000 bytes)
1.3 Protocol-Specific Vulnerabilities [OR]
1.3.1 QUIC Protocol Exploitation (DoQ) [OR]
1.3.1.1 Connection migration hijacking
1.3.1.2 Stream priority manipulation
1.3.1.3 QUIC spin bit side-channel
1.3.2 HTTP/2 Exploitation (DoH) [OR]
1.3.2.1 HPACK header compression attacks
1.3.2.2 Server push cache poisoning
1.3.2.3 Stream dependency manipulation
1.3.3 TLS Session Attacks (DoT) [OR]
1.3.3.1 Session ticket stealing
1.3.3.2 Pre-shared key exhaustion
1.3.3.3 Certificate transparency log poisoning
2. Attack Encrypted DNS [OR]
2.1 Privacy Leaks [OR]
2.1.1 Metadata Correlation [AND]
2.1.1.1 IP + timestamp correlation across multiple resolvers
2.1.1.2 Query size and timing analysis
2.1.1.3 Server name indication (SNI) monitoring
2.1.2 ML-based fingerprinting [OR]
2.1.2.1 Neural network traffic analysis
2.1.2.2 Query pattern recognition
2.1.2.3 Encrypted traffic classification
2.1.3 Protocol Identification [OR]
2.1.3.1 DoH/DoT/DoQ protocol fingerprinting
2.1.3.2 Application-level protocol detection
2.1.3.3 Middlebox cooperation for traffic analysis
2.2 Downgrade Attacks [AND]
2.2.1 Force fallback to plaintext DNS [OR]
2.2.1.1 TCP RST injection on port 853 (DoT)
2.2.1.2 HTTP/2 GOAWAY frame injection (DoH)
2.2.1.3 QUIC connection close spoofing (DoQ)
2.2.2 Encryption Bypass [OR]
2.2.2.1 Disable ECH (Encrypted Client Hello) in DoH
2.2.2.2 TLS version downgrade attacks
2.2.2.3 QUIC version negotiation manipulation
2.2.3 Middlebox Interference [OR]
2.2.3.1 ISP-level protocol blocking
2.2.3.2 Enterprise firewall policy enforcement
2.2.3.3 Government-mandated protocol filtering
2.3 Certificate Attacks [OR]
2.3.1 CA Compromise [OR]
2.3.1.1 Rogue certificate issuance
2.3.1.2 Intermediate CA exploitation
2.3.1.3 Certificate transparency log poisoning
2.3.2 Client Validation Bypass [OR]
2.3.2.1 Self-signed certificate acceptance
2.3.2.2 Certificate pinning bypass
2.3.2.3 Trust store manipulation
3. Cloud/SaaS Exploits [OR]
3.1 Kubernetes DNS Compromise [AND]
3.1.1 CoreDNS/Etdncache Poisoning [OR]
3.1.1.1 API server compromise
3.1.1.2 ConfigMap manipulation
3.1.1.3 Plugin vulnerability exploitation
3.1.2 NetworkPolicy Bypass [OR]
3.1.2.1 Privileged pod escape
3.1.2.2 Node-level network access
3.1.2.3 Cross-namespace traffic interception
3.1.3 Service Mesh Exploitation [OR]
3.1.3.1 Istio/Linkerd DNS redirection
3.1.3.2 mTLS certificate theft
3.1.3.3 Sidecar proxy manipulation
3.2 Serverless Abuse [OR]
3.2.1 DNS Tunneling [OR]
3.2.1.1 Lambda TXT record exfiltration
3.2.1.2 Cloud Functions DNS over HTTPS
3.2.1.3 Azure Functions private resolver abuse
3.2.2 Resource Exhaustion [OR]
3.2.2.1 DNS query burst attacks
3.2.2.2 Recursion depth exploitation
3.2.2.3 Cache saturation attacks
3.2.3 Cloud Integration Attacks [OR]
3.2.3.1 AWS Route 53 resolver hijacking
3.2.3.2 Google Cloud DNS API abuse
3.2.3.3 Azure Private DNS zone poisoning
3.3 Container Registry Attacks [OR]
3.3.1 Image Pull Manipulation [OR]
3.3.1.1 DNS spoofing for registry redirection
3.3.1.2 MITM attacks on image downloads
3.3.1.3 Cache poisoning for malicious images
3.3.2 Supply Chain Compromise [OR]
3.3.2.1 Malicious library injection via DNS
3.3.2.2 Dependency confusion attacks
3.3.2.3 Package manager DNS hijacking
4. Supply Chain Attacks [OR]
4.1 Registrar Hijacking [AND]
4.1.1 API Key Compromise [OR]
4.1.1.1 Cloudflare token theft
4.1.1.2 AWS Route 53 key leakage
4.1.1.3 Google Domains API abuse
4.1.2 Social Engineering [OR]
4.1.2.1 Registrar support impersonation
4.1.2.2 Post-GDPR WHOIS information gaps
4.1.2.3 Phone number porting attacks
4.1.3 Registry System Attacks [OR]
4.1.3.1 EPP protocol exploitation
4.1.3.2 Registry lock bypass
4.1.3.3 Transfer process manipulation
4.2 Subdomain Takeover [AND]
4.2.1 Dangling Resource Identification [OR]
4.2.1.1 CNAME mapping to unused cloud resources
4.2.1.2 NS record pointing to decommissioned servers
4.2.1.3 MX record targeting disabled services
4.2.2 Malicious Content Deployment [OR]
4.2.2.1 GitHub Pages site cloning
4.2.2.2 S3 bucket takeover
4.2.2.3 Azure Blob Storage hijacking
4.2.3 Persistence Mechanisms [OR]
4.2.3.1 SSL certificate procurement
4.2.3.2 DNS record obfuscation
4.2.3.3 Monitoring evasion techniques
4.3 CDN Compromise [OR]
4.3.1 DNS-Based CDN Manipulation [OR]
4.3.1.1 Edge server cache poisoning
4.3.1.2 Origin DNS spoofing
4.3.1.3 GeoDNS manipulation
4.3.2 Certificate Manipulation [OR]
4.3.2.1 SAN certificate abuse
4.3.2.2 CDN SSL termination bypass
4.3.2.3 Multi-CDN configuration conflicts
5. AI/ML-Augmented Attacks [OR]
5.1 Evasion Techniques [AND]
5.1.1 Reputation System Poisoning [OR]
5.1.1.1 DNS query pattern manipulation
5.1.1.2 Behavioral model contamination
5.1.1.3 Feedback loop exploitation
5.1.2 Query Obfuscation [OR]
5.1.2.1 GAN-generated benign-looking queries
5.1.2.2 CDN traffic mimicry
5.1.2.3 Legitimate domain spoofing
5.1.3 Adaptive Attacks [OR]
5.1.3.1 Reinforcement learning for evasion
5.1.3.2 Genetic algorithm optimization
5.1.3.3 Transfer learning across networks
5.2 Phishing Automation [AND]
5.2.1 Domain Generation [OR]
5.2.1.1 LLM-generated homograph domains
5.2.1.2 Context-aware typosquatting
5.2.1.3 Cultural adaptation algorithms
5.2.2 Infrastructure Management [OR]
5.2.2.1 Dynamic DNS fast-flux networks
5.2.2.2 Automated certificate procurement
5.2.2.3 Multi-CDN abuse for resilience
5.2.3 Target Identification [OR]
5.2.3.1 NLP-based brand monitoring
5.2.3.2 Social media sentiment analysis
5.2.3.3 Employee behavior prediction
6. Post-Quantum Threats [OR]
6.1 Cryptographic Harvesting [AND]
6.1.1 DNSSEC Record Collection [OR]
6.1.1.1 ECDSA-P256 signature harvesting
6.1.1.2 RSA-2048 key storage
6.1.1.3 NSEC3 chain enumeration
6.1.2 Quantum Decryption Preparation [OR]
6.1.2.1 Long-term encrypted data storage
6.1.2.2 Future decryption capability planning
6.1.2.3 Harvest-then-decrypt campaigns
6.1.3 Transition Period Exploitation [OR]
6.1.3.1 Algorithm confusion attacks
6.1.3.2 Hybrid scheme weaknesses
6.1.3.3 Backward compatibility exploitation
6.2 Quantum Key Distribution Attacks [OR]
6.2.1 QKD Protocol Exploitation [OR]
6.2.1.1 Photon-splitting attacks
6.2.1.2 Fake state attacks
6.2.1.3 Trojans in QKD hardware
6.2.2 Implementation Vulnerabilities [OR]
6.2.2.1 Side-channel attacks on QKD systems
6.2.2.2 Laser intensity manipulation
6.2.2.3 Detector blinding attacks
6.2.3 Integration Attacks [OR]
6.2.3.1 Classical-quantum interface exploitation
6.2.3.2 Key management system compromise
6.2.3.3 Quantum network routing attacks
7. Data Exfiltration Techniques [OR]
7.1 DNS Tunneling [AND]
7.1.1 Protocol Selection [OR]
7.1.1.1 Traditional DNS (TXT, NULL records)
7.1.1.2 DoH/DoT/DoQ encrypted tunneling
7.1.1.3 ICMP-based DNS manipulation
7.1.2 Evasion Methods [OR]
7.1.2.1 Query rate limiting bypass
7.1.2.2 Legitimate traffic blending
7.1.2.3 Multiple resolver rotation
7.1.3 Data Encoding [OR]
7.1.3.1 Base32/64 encoding variations
7.1.3.2 Compression with error correction
7.1.3.3 Fragmentation and reassembly
7.2 Covert Channels [OR]
7.2.1 Timing-Based Exfiltration [OR]
7.2.1.1 Query response timing modulation
7.2.1.2 DNS refresh interval exploitation
7.2.1.3 TTL value manipulation
7.2.2 Storage Channels [OR]
7.2.2.1 DNS cache poisoning with data
7.2.2.2 NSEC3 gap exploitation
7.2.2.3 DNSSEC signature embedding
7.2.3 Behavioral Patterns [OR]
7.2.3.1 Query sequence encoding
7.2.3.2 Resolver selection patterns
7.2.3.3 Domain name generation algorithms
7.3 Exfiltration Infrastructure [OR]
7.3.1 Command and Control [OR]
7.3.1.1 Dynamic domain generation
7.3.1.2 DNS-based payload delivery
7.3.1.3 Dead drop resolvers
7.3.2 Data Processing [OR]
7.3.2.1 Distributed exfiltration aggregation
7.3.2.2 On-the-fly decoding services
7.3.2.3 Cloud function data processing
7.3.3 Persistence Mechanisms [OR]
7.3.3.1 Multiple exfiltration pathways
7.3.3.2 Fallback communication channels
7.3.3.3 Anti-forensic techniques
Attack tree risk assessment table¶
Attack Path ID |
Attack Path Description |
Technical Challenge |
Resources Required |
Overall Risk (T+R) |
---|---|---|---|---|
1. Exploit Protocol Weaknesses |
||||
1.1.1.1 |
Birthday attack on 16-bit TXID space |
Low |
Low (Scripts, network access) |
Low |
1.1.1.2 |
Timing attacks on resolver response handling |
Medium |
Medium (Precise tools, stable connection) |
Medium |
1.1.1.3 |
Fragment-based poisoning attacks |
High |
Medium (Specialized tools) |
High |
1.1.2.1 |
TLS padding oracle attacks on DoT |
High |
Medium (Cryptographic knowledge) |
High |
1.1.2.2 |
QUIC protocol timing analysis on DoQ |
High |
High (Specialized QUIC tools) |
High |
1.1.2.3 |
HTTP/2 stream correlation attacks on DoH |
Medium |
Medium (Traffic analysis tools) |
Medium |
1.1.3.1 |
NSEC/NSEC3 walking for zone enumeration |
Low |
Low (Scripts like |
Low |
1.1.3.2 |
RRSIG timing attacks for key recovery |
Very High |
High (Cryptographic expertise) |
Very High |
1.1.3.3 |
Algorithm downgrade attacks |
Medium |
Low (Packet crafting tools) |
Medium |
1.2.1.1 |
DoQ reflection with large TXT records |
Low |
Medium (List of open resolvers) |
Medium |
1.2.1.2 |
DoH POST request amplification |
Low |
Medium (List of open DoH resolvers) |
Medium |
1.2.1.3 |
DoT session resumption attacks |
Medium |
Medium (Traffic generation capacity) |
Medium |
1.2.2.1 |
NSEC3 response amplification |
Low |
Low (Scripts, open resolvers) |
Low |
1.2.2.2 |
Large RRSIG reflection attacks |
Low |
Low (Scripts, open resolvers) |
Low |
1.2.2.3 |
DNAME chain exploitation |
Medium |
Low (Specific DNS knowledge) |
Medium |
1.3.1.1 |
QUIC connection migration hijacking |
High |
High (QUIC stack access) |
High |
1.3.1.2 |
QUIC stream priority manipulation |
Medium |
Medium (QUIC knowledge) |
Medium |
1.3.1.3 |
QUIC spin bit side-channel |
High |
High (Traffic analysis expertise) |
High |
1.3.2.1 |
HTTP/2 HPACK compression attacks |
High |
High (HTTP/2 implementation knowledge) |
High |
1.3.2.2 |
HTTP/2 server push cache poisoning |
Medium |
Medium (Man-in-the-middle position) |
Medium |
1.3.2.3 |
HTTP/2 stream dependency manipulation |
High |
High (HTTP/2 expertise) |
High |
1.3.3.1 |
TLS session ticket stealing |
Medium |
Medium (MitM position) |
Medium |
1.3.3.2 |
Pre-shared key exhaustion |
Low |
Low (Scripts to spam connections) |
Low |
1.3.3.3 |
CT log poisoning |
Very High |
Very High (CA compromise required) |
Very High |
2. Attack Encrypted DNS |
||||
2.1.1.1 |
IP + timestamp correlation |
Low |
Medium (Access to multiple data sources) |
Medium |
2.1.1.2 |
Query size and timing analysis |
Medium |
Medium (Traffic capture & analysis) |
Medium |
2.1.1.3 |
SNI monitoring |
Low |
Low (Network position) |
Low |
2.1.2.1 |
Neural network traffic analysis |
Very High |
Very High (ML expertise, data, compute) |
Very High |
2.1.2.2 |
Query pattern recognition |
High |
High (ML expertise, data) |
High |
2.1.2.3 |
Encrypted traffic classification |
High |
High (ML expertise, data) |
High |
2.1.3.1 |
DoH/DoT/DoQ protocol fingerprinting |
Medium |
Medium (Traffic analysis tools) |
Medium |
2.1.3.2 |
Application-level protocol detection |
Medium |
Medium (Traffic analysis tools) |
Medium |
2.1.3.3 |
Middlebox cooperation |
Low |
High (Requires privileged ISP/state actor access) |
High |
2.2.1.1 |
TCP RST injection on port 853 |
Low |
Low (Network access) |
Low |
2.2.1.2 |
HTTP/2 GOAWAY frame injection |
Medium |
Medium (MitM position) |
Medium |
2.2.1.3 |
QUIC connection close spoofing |
Medium |
Medium (MitM position) |
Medium |
2.2.2.1 |
Disable ECH in DoH |
Low |
Low (Client-side manipulation) |
Low |
2.2.2.2 |
TLS version downgrade |
Medium |
Medium (MitM position, tools) |
Medium |
2.2.2.3 |
QUIC version negotiation manipulation |
High |
Medium (MitM position, QUIC knowledge) |
High |
2.2.3.1 |
ISP-level protocol blocking |
Low |
Very High (Requires ISP-level control) |
Very High |
2.2.3.2 |
Enterprise firewall policy enforcement |
Low |
High (Requires enterprise network control) |
High |
2.2.3.3 |
Government-mandated filtering |
Low |
Extreme (Requires nation-state authority) |
Extreme |
2.3.1.1 |
Rogue certificate issuance |
Very High |
Extreme (Requires CA compromise) |
Extreme |
2.3.1.2 |
Intermediate CA exploitation |
Very High |
Extreme (Requires CA compromise) |
Extreme |
2.3.1.3 |
CT log poisoning |
Very High |
Very High (Extremely difficult) |
Very High |
2.3.2.1 |
Self-signed certificate acceptance |
Low |
Low (Social engineering or malware) |
Low |
2.3.2.2 |
Certificate pinning bypass |
High |
Medium (Reverse engineering skills) |
High |
2.3.2.3 |
Trust store manipulation |
High |
High (OS/admin-level access) |
High |
3. Cloud/SaaS Exploits |
||||
3.1.1.1 |
API server compromise |
High |
High (K8s exploit chain) |
High |
3.1.1.2 |
ConfigMap manipulation |
Medium |
High (K8s RBAC bypass) |
High |
3.1.1.3 |
Plugin vulnerability exploitation |
Medium |
Medium (Specific exploit) |
Medium |
3.1.2.1 |
Privileged pod escape |
High |
High (K8s/container expertise) |
High |
3.1.2.2 |
Node-level network access |
High |
High (Pod-to-node escape) |
High |
3.1.2.3 |
Cross-namespace traffic interception |
Medium |
Medium (NetworkPolicy misconfig) |
Medium |
3.1.3.1 |
Istio/Linkerd DNS redirection |
High |
High (Service mesh expertise) |
High |
3.1.3.2 |
mTLS certificate theft |
High |
High (Service mesh expertise) |
High |
3.1.3.3 |
Sidecar proxy manipulation |
High |
High (Service mesh expertise) |
High |
3.2.1.1 |
Lambda TXT record exfiltration |
Low |
Low (Scripting, DNS access) |
Low |
3.2.1.2 |
Cloud Functions over DoH |
Medium |
Low (Scripting, cloud account) |
Medium |
3.2.1.3 |
Azure private resolver abuse |
Medium |
Medium (Azure access, knowledge) |
Medium |
3.2.2.1 |
DNS query burst attacks |
Low |
Low (Scripts, cloud function) |
Low |
3.2.2.2 |
Recursion depth exploitation |
Medium |
Low (Specific payload) |
Medium |
3.2.2.3 |
Cache saturation attacks |
Low |
Medium (Resource budget for queries) |
Medium |
3.2.3.1 |
AWS Route 53 resolver hijacking |
High |
High (AWS account compromise) |
High |
3.2.3.2 |
Google Cloud DNS API abuse |
High |
High (GCP account compromise) |
High |
3.2.3.3 |
Azure Private DNS zone poisoning |
High |
High (Azure account compromise) |
High |
3.3.1.1 |
DNS spoofing for registry redirection |
Medium |
Medium (MitM on network) |
Medium |
3.3.1.2 |
MITM on image downloads |
Medium |
Medium (MitM position) |
Medium |
3.3.1.3 |
Cache poisoning for malicious images |
High |
High (Registry/DNS compromise) |
High |
3.3.2.1 |
Malicious library injection via DNS |
Medium |
Medium (Supply chain access) |
Medium |
3.3.2.2 |
Dependency confusion attacks |
Low |
Medium (Public repo, internal name) |
Medium |
3.3.2.3 |
Package manager DNS hijacking |
High |
High (MitM or DNS compromise) |
High |
4. Supply Chain Attacks |
||||
4.1.1.1 |
Cloudflare token theft |
Medium |
Medium (Phishing, malware) |
Medium |
4.1.1.2 |
AWS Route 53 key leakage |
Medium |
Medium (Misconfig, credential leak) |
Medium |
4.1.1.3 |
Google Domains API abuse |
Medium |
Medium (Credential theft) |
Medium |
4.1.2.1 |
Registrar support impersonation |
Low |
Low (Social engineering skills) |
Low |
4.1.2.2 |
WHOIS information gaps |
Low |
Low (OSINT research) |
Low |
4.1.2.3 |
Phone number porting attacks |
Medium |
Medium (SS7 flaws, social engineering) |
Medium |
4.1.3.1 |
EPP protocol exploitation |
High |
High (Registrar-specific knowledge) |
High |
4.1.3.2 |
Registry lock bypass |
Very High |
Extreme (Extremely difficult, often insiders) |
Extreme |
4.1.3.3 |
Transfer process manipulation |
Medium |
Medium (Social engineering, flaws) |
Medium |
4.2.1.1 |
CNAME to unused cloud resources |
Low |
Low (Scanners like |
Low |
4.2.1.2 |
NS to decommissioned servers |
Low |
Low (DNS auditing) |
Low |
4.2.1.3 |
MX to disabled services |
Low |
Low (DNS auditing) |
Low |
4.2.2.1 |
GitHub Pages takeover |
Low |
Low (GitHub account) |
Low |
4.2.2.2 |
S3 bucket takeover |
Low |
Low (AWS account) |
Low |
4.2.2.3 |
Azure Blob hijacking |
Low |
Low (Azure account) |
Low |
4.2.3.1 |
SSL certificate procurement |
Low |
Low (LetsEncrypt, etc.) |
Low |
4.2.3.2 |
DNS record obfuscation |
Low |
Low (Knowledge of DNS) |
Low |
4.2.3.3 |
Monitoring evasion |
Medium |
Low (Timing, low traffic) |
Medium |
4.3.1.1 |
Edge server cache poisoning |
High |
High (CDN-specific knowledge) |
High |
4.3.1.2 |
Origin DNS spoofing |
Medium |
High (Origin compromise/MitM) |
High |
4.3.1.3 |
GeoDNS manipulation |
High |
High (CDN config compromise) |
High |
4.3.2.1 |
SAN certificate abuse |
Medium |
Medium (CDN config access) |
Medium |
4.3.2.2 |
CDN SSL termination bypass |
High |
High (CDN-specific vulnerability) |
High |
4.3.2.3 |
Multi-CDN configuration conflicts |
High |
High (Complex setup knowledge) |
High |
5. AI/ML-Augmented Attacks |
||||
5.1.1.1 |
DNS query pattern manipulation |
High |
High (ML/Adversarial AI expertise) |
High |
5.1.1.2 |
Behavioral model contamination |
Very High |
Very High (ML expertise, platform access) |
Very High |
5.1.1.3 |
Feedback loop exploitation |
High |
High (ML expertise, system knowledge) |
High |
5.1.2.1 |
GAN-generated queries |
Very High |
Very High (GAN/ML expertise, compute) |
Very High |
5.1.2.2 |
CDN traffic mimicry |
High |
High (Traffic analysis, ML) |
High |
5.1.2.3 |
Legitimate domain spoofing |
Medium |
Low (Existing tools, slight modification) |
Medium |
5.1.3.1 |
RL for evasion |
Very High |
Extreme (RL/ML expertise, significant compute) |
Extreme |
5.1.3.2 |
Genetic algorithm optimization |
Very High |
Very High (ML expertise, compute) |
Very High |
5.1.3.3 |
Transfer learning |
Very High |
Very High (ML expertise, diverse datasets) |
Very High |
5.2.1.1 |
LLM-generated homograph domains |
Low |
Low (Access to LLM API) |
Low |
5.2.1.2 |
Context-aware typosquatting |
Medium |
Medium (NLP/OSINT skills) |
Medium |
5.2.1.3 |
Cultural adaptation algorithms |
High |
High (NLP, cultural datasets) |
High |
5.2.2.1 |
Dynamic DNS fast-flux |
Medium |
Medium (Botnet, scripts) |
Medium |
5.2.2.2 |
Automated certificate procurement |
Low |
Low (Scripts, ACME API) |
Low |
5.2.2.3 |
Multi-CDN abuse |
High |
High (Resources to use multiple CDNs) |
High |
5.2.3.1 |
NLP-based brand monitoring |
Medium |
Medium (NLP skills, scraping) |
Medium |
5.2.3.2 |
Social media sentiment analysis |
Medium |
Medium (NLP skills, API access) |
Medium |
5.2.3.3 |
Employee behavior prediction |
Very High |
Very High (Advanced ML, internal data) |
Very High |
6. Post-Quantum Threats |
||||
6.1.1.1 |
ECDSA-P256 signature harvesting |
Low |
Low (Passive DNS collection) |
Low |
6.1.1.2 |
RSA-2048 key storage |
Low |
Medium (Storage capacity for large keys) |
Medium |
6.1.1.3 |
NSEC3 chain enumeration |
Low |
Low (Scripts) |
Low |
6.1.2.1 |
Long-term encrypted data storage |
Low |
High (Massive storage infrastructure) |
High |
6.1.2.2 |
Future decryption capability planning |
N/A |
Extreme (Nation-state level investment) |
Extreme |
6.1.2.3 |
Harvest-then-decrypt campaigns |
Low |
Extreme (See above) |
Extreme |
6.1.3.1 |
Algorithm confusion attacks |
High |
High (PQ crypto expertise) |
High |
6.1.3.2 |
Hybrid scheme weaknesses |
High |
High (PQ crypto expertise) |
High |
6.1.3.3 |
Backward compatibility exploitation |
Medium |
Medium (Protocol downgrade attacks) |
Medium |
6.2.1.1 |
Photon-splitting attacks |
Extreme |
Extreme (Quantum physics expertise) |
Extreme |
6.2.1.2 |
Fake state attacks |
Extreme |
Extreme (Quantum physics expertise) |
Extreme |
6.2.1.3 |
Trojans in QKD hardware |
Extreme |
Extreme (State-level hardware sabotage) |
Extreme |
6.2.2.1 |
Side-channels on QKD systems |
Extreme |
Extreme (Quantum engineering) |
Extreme |
6.2.2.2 |
Laser intensity manipulation |
Very High |
Extreme (Specialized lab equipment) |
Extreme |
6.2.2.3 |
Detector blinding attacks |
Very High |
Extreme (Specialized lab equipment) |
Extreme |
6.2.3.1 |
Classical-quantum interface exploitation |
Extreme |
Extreme (Unique expertise) |
Extreme |
6.2.3.2 |
Key management system compromise |
High |
High (Traditional infosec + QKD knowledge) |
High |
6.2.3.3 |
Quantum network routing attacks |
Extreme |
Extreme (Quantum networking expertise) |
Extreme |
7. Data Exfiltration Techniques |
||||
7.1.1.1 |
Traditional DNS tunneling |
Low |
Low (Off-the-shelf tools) |
Low |
7.1.1.2 |
DoH/DoT/DoQ encrypted tunneling |
Medium |
Low (Modified tools) |
Medium |
7.1.1.3 |
ICMP-based DNS manipulation |
Medium |
Medium (Custom tools, privileges) |
Medium |
7.1.2.1 |
Query rate limiting bypass |
Medium |
Low (Slow channel, patience) |
Medium |
7.1.2.2 |
Legitimate traffic blending |
High |
Medium (Traffic analysis, careful planning) |
High |
7.1.2.3 |
Multiple resolver rotation |
Low |
Low (List of resolvers) |
Low |
7.1.3.1 |
Base32/64 encoding |
Low |
Low (Standard encoding) |
Low |
7.1.3.2 |
Compression with error correction |
Medium |
Medium (Custom client/server) |
Medium |
7.1.3.3 |
Fragmentation and reassembly |
Medium |
Medium (Custom client/server) |
Medium |
7.2.1.1 |
Query response timing modulation |
High |
High (Stable channel, precise control) |
High |
7.2.1.2 |
DNS refresh interval exploitation |
Medium |
Medium (Knowledge of client behavior) |
Medium |
7.2.1.3 |
TTL value manipulation |
Low |
Low (Control of authoritative server) |
Low |
7.2.2.1 |
DNS cache poisoning with data |
High |
High (Cache poisoning expertise) |
High |
7.2.2.2 |
NSEC3 gap exploitation |
Medium |
Medium (DNSSEC knowledge) |
Medium |
7.2.2.3 |
DNSSEC signature embedding |
Very High |
High (Cryptographic expertise) |
Very High |
7.2.3.1 |
Query sequence encoding |
Medium |
Medium (Custom algorithm) |
Medium |
7.2.3.2 |
Resolver selection patterns |
Low |
Low (Client configuration control) |
Low |
7.2.3.3 |
Domain name generation algorithms |
Low |
Low (Standard DGA) |
Low |
7.3.1.1 |
Dynamic domain generation |
Low |
Low (DGA script) |
Low |
7.3.1.2 |
DNS-based payload delivery |
Low |
Low (Authoritative server control) |
Low |
7.3.1.3 |
Dead drop resolvers |
Medium |
Medium (Compromised resolver) |
Medium |
7.3.2.1 |
Distributed exfiltration aggregation |
High |
High (Multiple nodes, coordination) |
High |
7.3.2.2 |
On-the-fly decoding services |
Medium |
Medium (Cloud function/script) |
Medium |
7.3.2.3 |
Cloud function data processing |
Medium |
Medium (Cloud account) |
Medium |
7.3.3.1 |
Multiple exfiltration pathways |
Medium |
Medium (Redundant infrastructure) |
Medium |
7.3.3.2 |
Fallback communication channels |
Medium |
Medium (Additional C2 setup) |
Medium |
7.3.3.3 |
Anti-forensic techniques |
High |
High (Expertise in forensics) |
High |
Risk Assessment Legend¶
Technical Challenge: The level of expertise, knowledge, and skill required to execute the attack.
Resources Required: The tools, infrastructure, access, and time needed.
Overall Risk (T+R): A combined assessment of how feasible the attack is for a threat actor to carry out. This is not likelihood or impact, but a measure of the barrier to entry. A “Low” overall risk means it’s easy to execute; “Extreme” means it is currently only feasible for the most advanced actors (e.g., nation-states).