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• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-33324 • published on May 5, 2026 SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.
• CVE-2026-32936 • published on May 5, 2026 CoreDNS is a DNS server that chains plugins. In versions prior to 1.14.3, the DNS-over-HTTPS (DoH) GET path accepts oversized dns= query parameter values and performs URL query parsing, base64 decoding, and DNS message unpacking before rejecting the request. Unlike the POST path, which applies a bounded read via http.MaxBytesReader limited to 65536 bytes, the GET path has no equivalent size validation before expensive processing. A remote, unauthenticated attacker can repeatedly send oversized DoH GET requests to force high CPU usage, large transient memory allocations, and elevated garbage-collection pressure, leading to denial of service. This issue has been fixed in version 1.14.3.
• CVE-2026-32936 • published on May 5, 2026 CoreDNS is a DNS server that chains plugins. In versions prior to 1.14.3, the DNS-over-HTTPS (DoH) GET path accepts oversized dns= query parameter values and performs URL query parsing, base64 decoding, and DNS message unpacking before rejecting the request. Unlike the POST path, which applies a bounded read via http.MaxBytesReader limited to 65536 bytes, the GET path has no equivalent size validation before expensive processing. A remote, unauthenticated attacker can repeatedly send oversized DoH GET requests to force high CPU usage, large transient memory allocations, and elevated garbage-collection pressure, leading to denial of service. This issue has been fixed in version 1.14.3.
• CVE-2026-32936 • published on May 5, 2026 CoreDNS is a DNS server that chains plugins. In versions prior to 1.14.3, the DNS-over-HTTPS (DoH) GET path accepts oversized dns= query parameter values and performs URL query parsing, base64 decoding, and DNS message unpacking before rejecting the request. Unlike the POST path, which applies a bounded read via http.MaxBytesReader limited to 65536 bytes, the GET path has no equivalent size validation before expensive processing. A remote, unauthenticated attacker can repeatedly send oversized DoH GET requests to force high CPU usage, large transient memory allocations, and elevated garbage-collection pressure, leading to denial of service. This issue has been fixed in version 1.14.3.
• CVE-2026-32936 • published on May 5, 2026 CoreDNS is a DNS server that chains plugins. In versions prior to 1.14.3, the DNS-over-HTTPS (DoH) GET path accepts oversized dns= query parameter values and performs URL query parsing, base64 decoding, and DNS message unpacking before rejecting the request. Unlike the POST path, which applies a bounded read via http.MaxBytesReader limited to 65536 bytes, the GET path has no equivalent size validation before expensive processing. A remote, unauthenticated attacker can repeatedly send oversized DoH GET requests to force high CPU usage, large transient memory allocations, and elevated garbage-collection pressure, leading to denial of service. This issue has been fixed in version 1.14.3.
• CVE-2026-32936 • published on May 5, 2026 CoreDNS is a DNS server that chains plugins. In versions prior to 1.14.3, the DNS-over-HTTPS (DoH) GET path accepts oversized dns= query parameter values and performs URL query parsing, base64 decoding, and DNS message unpacking before rejecting the request. Unlike the POST path, which applies a bounded read via http.MaxBytesReader limited to 65536 bytes, the GET path has no equivalent size validation before expensive processing. A remote, unauthenticated attacker can repeatedly send oversized DoH GET requests to force high CPU usage, large transient memory allocations, and elevated garbage-collection pressure, leading to denial of service. This issue has been fixed in version 1.14.3.
• CVE-2026-32936 • published on May 5, 2026 CoreDNS is a DNS server that chains plugins. In versions prior to 1.14.3, the DNS-over-HTTPS (DoH) GET path accepts oversized dns= query parameter values and performs URL query parsing, base64 decoding, and DNS message unpacking before rejecting the request. Unlike the POST path, which applies a bounded read via http.MaxBytesReader limited to 65536 bytes, the GET path has no equivalent size validation before expensive processing. A remote, unauthenticated attacker can repeatedly send oversized DoH GET requests to force high CPU usage, large transient memory allocations, and elevated garbage-collection pressure, leading to denial of service. This issue has been fixed in version 1.14.3.
• CVE-2026-32936 • published on May 5, 2026 CoreDNS is a DNS server that chains plugins. In versions prior to 1.14.3, the DNS-over-HTTPS (DoH) GET path accepts oversized dns= query parameter values and performs URL query parsing, base64 decoding, and DNS message unpacking before rejecting the request. Unlike the POST path, which applies a bounded read via http.MaxBytesReader limited to 65536 bytes, the GET path has no equivalent size validation before expensive processing. A remote, unauthenticated attacker can repeatedly send oversized DoH GET requests to force high CPU usage, large transient memory allocations, and elevated garbage-collection pressure, leading to denial of service. This issue has been fixed in version 1.14.3.