Effective Strategies to Counter High-Volume AWS Bot Traffic

High-volume bot traffic, especially when emanating from major cloud providers like AWS and seemingly immune to standard abuse reports, presents a significant challenge. Such persistent activity can escalate operational costs, skew analytics, and demand a range of creative and often aggressive countermeasures beyond typical blocking. This discussion explored various strategies to combat a bot sending 2 billion requests per month from AWS Singapore, which identified itself as 'Mozilla/5.0 (compatible; crawler)' and proved resistant to standard 4XX responses and 30X redirects.

Aggressive Blocking at the Edge

One of the most direct approaches involves enhancing blocking mechanisms at the network edge, ideally through services like Cloudflare. Instead of merely serving 4XX responses, which still consume some resources, dropping packets entirely can be more efficient. A common suggestion is to block entire IP ranges or Autonomous System Numbers (ASNs) associated with the bot's origin, such as AWS Singapore. This is particularly effective if there's no legitimate traffic expected from those specific cloud regions or ASNs.

Caveats: Blocking broad ranges carries the risk of inadvertently affecting legitimate users or critical services, including search engine crawlers (e.g., Googlebot), which could lead to service disruptions or issues like Google Ads account suspensions. Keeping up with dynamic IP ranges from cloud providers also requires automated updates.

Resource Exhaustion Tactics (Tarpitting and Slow Responses)

An intriguing and proven strategy is to turn the tables on the bot by making its requests resource-intensive for the bot operator. This involves what's sometimes called "tarpitting" or an "inverse Slow Loris" attack, where the defending server deliberately prolongs connections.

Implementation: Instead of rejecting a connection, the server accepts it but sends the response data extremely slowly—for instance, one character every 10 to 30 seconds. This forces the bot to keep connections open for extended periods, consuming its local port resources and exhausting its worker pool, thus limiting the number of new requests it can make.
Effectiveness: The original poster successfully tested this method by redirecting traffic to a small VPS configured to keep connections open and send data slowly, observing a substantial drop in the bot's activity.
Considerations: While effective, this method can raise concerns about violating the Terms of Service (ToS) of one's own hosting or CDN provider, as it can be interpreted as a form of retaliatory abuse.

Cost Imposition and Data Poisoning via Redirects

Leveraging the bot's behavior of following 30X redirects, several strategies aim to impose costs or corrupt the data it collects.

Redirect to Large Files or Gzip Bombs: The bot can be redirected to extremely large files (e.g., Windows ISOs or Linux images) hosted by the bot's own cloud provider (like AWS itself) to incur significant egress bandwidth costs for the attacker. Alternatively, a "gzip bomb"—a small compressed file that expands into petabytes of data upon decompression—can be used to overwhelm the bot's memory and crash its processes.
Redirect to Self or Blackholes: Redirecting the bot back to its own IP address or to unassigned/blackholed IP spaces causes it to waste its own resources attempting to connect to non-existent services, effectively idling it out.
Data Poisoning: For bots scraping content (e.g., pricing data for competitors or training AI models), feeding subtly inaccurate or randomly fudged data can render the collected information useless or even harmful to the attacker.
Ethical/Legal Considerations: While tempting, redirecting to illegal or shock sites carries significant legal and ethical risks for the defender. Even other forms of retaliation should be carefully considered against potential ToS violations.

Legal and Abuse Channels

When technical solutions are complex or abuse reports are ignored, legal pressure can be a powerful tool.

Escalated Abuse Reports: Standard abuse reports to AWS were initially ineffective, suggesting that a more forceful approach is needed. Framing the traffic as a Denial of Service (DoS) attack, especially when it leads to renegotiating contracts and increased costs, can strengthen the case.
Legal Demand Letters: Engaging a lawyer to send a formal demand letter to AWS, explicitly detailing the financial damages and threatening legal action (e.g., under the Computer Fraud and Abuse Act), often compels AWS to take the matter more seriously. The threat of legal discovery to identify the underlying client can motivate AWS to act against its abusive customer.
Local Regulatory Reports: If the bot can be redirected to content illegal in its operating region (e.g., pornographic material in Singapore), reporting this activity to local communications regulators might also trigger action against the bot operator or AWS.

Other Mitigations

Proof-of-Work (PoW) Challenges: Implementing PoW checks can filter out high-volume automated requests, though they can introduce friction and negatively impact legitimate user experience.
User-Agent Filtering: While easily spoofed, blocking specific user-agents (like the 'Mozilla/5.0 (compatible; crawler)' in this case) can deter less sophisticated bots.
robots.txt and 429 Responses: Even if a malicious bot ignores robots.txt or 429 (Too Many Requests) HTTP status codes, serving these can bolster a legal or abuse report by demonstrating clear attempts to politely request the bot to cease activity.

Combating persistent, high-volume bot traffic requires a multi-faceted approach. This often involves blending aggressive technical countermeasures to make the bot's operation costly or ineffective with strategic legal pressure to compel action from cloud providers who might otherwise remain unresponsive.