What technical methods do ISPs use to detect CSAM traffic on their networks?
Executive summary
ISPs use an array of network- and content-level techniques to detect and block child sexual abuse material (CSAM), most commonly URL and DNS blocklists, hash‑matching of known images/video fingerprints, and web‑filtering or routing appliances that drop or redirect traffic to flagged hosts (examples: IWF lists, PhotoDNA/hash databases, and BGP/out‑of‑band filters) [1] [2] [3]. Industry groups report wide voluntary use of image and video hash matchers—89% of Tech Coalition members use at least one image hash matcher and NCMEC has shared millions of known CSAM hashes with service providers—while vendors and national guidance push ISPs toward URL filtering, routing controls, and proactive scanning where lawful [2] [4] [1].
1. Blocklists and DNS/URL filtering: the first line of defense
Many ISPs subscribe to curated URL and DNS blocklists (for example lists maintained by the Internet Watch Foundation) and implement DNS or HTTP filtering to prevent access to known CSAM hosts; guidance from the UK government explicitly cites using IWF lists and warns ISPs to ensure new protocols don’t break filtering [1]. Vendors sell turnkey filtering solutions that integrate blocklists and enforce policies at scale; Netsweeper markets its product to ISPs as a means to scan and block CSAM sites and claim integration with routing controls and web filters [5] [3].
2. Hash‑matching: fingerprinting known content at scale
Hash matching remains the dominant method for identifying previously known CSAM: companies and infrastructure providers use digital fingerprints (hashes) such as PhotoDNA, MD5 variants, PDQ and other fuzzy or perceptual hashes to match images and videos against databases of confirmed CSAM [2] [6]. Industry data show broad voluntary adoption—89% of Tech Coalition members use image hash‑matching and NCMEC had shared over 9.8 million hashes with ESPs as of Dec. 31, 2024—enabling automated reporting to authorities when matches occur [2] [4].
3. Fuzzy hashing and content‑tolerant matching for altered media
Because simple cryptographic hashes change when images are cropped or filtered, ISPs and infrastructure tools increasingly use fuzzy/perceptual hashing that tolerates edits; Cloudflare’s CSAM scanning tool and other vendors explicitly use fuzzy hashing to detect altered images rather than relying on exact one‑to‑one matches [7] [8]. These methods increase catch rates for modified content but depend on robust, centrally maintained hash lists and risk false positives if not tuned carefully [7].
4. Network routing and blocking (BGP/out‑of‑band filtering)
Some commercial products couple routing controls and out‑of‑band web filtering so ISPs can intercept or reroute traffic to block access to offending domains rapidly; vendors advertise combining BGP routing with filtering appliances to stop CSAM distribution across operator networks [3]. Government guidance and industry vendors promote these approaches as scalable ways for infrastructure providers to enforce take‑down or blocking orders [1] [3].
5. Client‑side and voluntary scanning vs. legislative mandates
Private sector initiatives predominate: many tech companies and infrastructure providers voluntarily deploy detection tools and report to hotlines like NCMEC, but legislative landscapes vary. The EU Council recently moved away from mandatory scanning requirements for global tech firms in proposed online child protection legislation, removing enforced scanning of encrypted materials—showing policy is still evolving and that voluntary industry practices coexist with selective legal obligations [9] [2].
6. Limitations, evasion, and the underground response
Technical detection is effective against known content and public web hosts but less so against actors using encryption, peer‑to‑peer networks, Tor, VPNs, or private messaging; academic research finds prolific CSAM distribution on both clear‑web platforms and privacy‑oriented networks, and offenders adopt measures specifically to evade detection [10] [11]. Hash lists cannot catch novel material until it is discovered and hashed, and client‑side or server‑side scanning raises tradeoffs around privacy, false positives, and scope [2] [12].
7. Conflicting incentives and hidden agendas in the marketplace
Vendors selling filtering and scanning tools have a commercial incentive to promote their solutions—Netsweeper and similar firms position products as corporate responsibility and compliance tools—while infrastructure providers balance legal obligations, customer privacy, and operational cost [5] [3]. Industry coalitions emphasize voluntary detection (Tech Coalition) and NCMEC’s hash sharing underpins much of private‑sector reporting; policymakers and privacy advocates contest where mandatory scanning would intrude on encryption and user privacy [2] [9].
Limitations: available sources describe the main technical methods and policy context but do not provide exhaustive technical specifications, comparative detection efficacy metrics, or operational legal frameworks for every jurisdiction; those details are not found in current reporting (not found in current reporting).