tls-tester
TLS tester is a class of automated scanning tools used to probe Transport Layer Security (TLS) endpoints for misconfigurations, weak cipher suites, and known vulnerabilities such as Heartbleed (CVE-2014-0160) and POODLE (CVE-2014-3566). While legitimate versions exist (e.g., testssl.sh, originally developed by Dirk Wetter and maintained on GitHub), malicious actors deploy customized forks that conduct unauthorized reconnaissance against web applications, often as a precursor to exploitation. These bots are characterized by their systematic enumeration of TLS handshake parameters and their ability to log and map certificate chains.
Malicious TLS tester bots perform deep packet inspection of SSL/TLS handshakes, checking for supported protocol versions (e.g., SSLv2, SSLv3, TLS 1.0–1.3) and weak cryptographic algorithms like export-grade ciphers (e.g., EXPORT_RSA). They can detect Heartbleed by sending oversized heartbeat requests and analyzing memory leak responses. Some variants also test for CRIME (CVE-2012-4929), BREACH (CVE-2013-3587), and Logjam (CVE-2015-4000) by manipulating TLS compression and key exchange parameters. The bot typically initiates a high volume of short-lived TCP connections, each terminating after a single handshake attempt, to avoid detection by connection-level rate limiting. It may also extract and store X.509 certificate metadata, including subject alternative names and issuer information, for later mapping of infrastructure.
Large-scale TLS scanning campaigns using malicious TLS tester bots were documented during the aftermath of the Heartbleed disclosure in April 2014, where attackers scanned over 1 million IP addresses to find vulnerable servers. In 2020, a wave of automated TLS probing targeted AWS Elastic Load Balancers, exploiting weak Diffie-Hellman parameters. The legitimate testssl.sh tool (GitHub: drwetter/testssl.sh, version 3.2) has been weaponized by red teams and hobbyist attackers alike, with source code analysis showing an option (--warnings off) that facilitates silent scanning without alerting server logs.
Common User-Agent strings include "Mozilla/5.0 (compatible; TLS Tester/1.0; +http://example.com/bot)" or "curl/7.68.0 (with OpenSSL) --tls-test". Behavioral fingerprints include rapid sequential connections to ports 443, 8443, and 465 with varying SNI (Server Name Indication) fields, and incomplete TLS handshakes that send ClientHello but immediately reset. Traffic often exhibits low entropy in cipher suite lists (e.g., always offering only vulnerable ciphers) and a monotonic source IP pattern across multiple targets.
Unauthorized TLS scanning by a malicious TLS tester can expose outdated certificates, expired protocols, and misconfigured cipher suites, providing attackers a roadmap for targeted exploits. If Heartbleed or similar memory-leak vulnerabilities are found, an attacker can extract private keys, session tokens, or plaintext payloads, leading to full compromise of encrypted communications. Repeated scans may also degrade server performance due to excessive handshake computation, especially on low-resource devices.
TLS tester is blocked immediately on detection because it is a reconnaissance tool that systematically probes for weaknesses that could enable subsequent data exfiltration or man-in-the-middle attacks. Web application firewalls (WAF) should drop traffic from known anomalous User-Agent patterns, enforce rate limiting on incomplete handshakes, and inspect cipher suite offers for known malicious fingerprints. Regular TLS auditing with legitimate tools is recommended to close vulnerabilities before attackers find them.
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ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the bots listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.
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