Summary pgjdbc is vulnerable to a client-side denial of service during SCRAM-SHA-256 authentication.
Impact A malicious server can instruct the driver to perform SCRAM authentication with a very large iteration count. With a large enough value, the client spends an unbounded amount of CPU time inside PBKDF2 before authentication can fail. A single attempt ties up a CPU core. Repeated or concurrent attempts exhaust client CPU and can wedge connection pools.
In affected versions, loginTimeout did not fully mitigate this problem. When loginTimeout expired, the caller could stop waiting, but the worker thread performing the connection attempt could continue running and burning CPU inside the SCRAM PBKDF2 computation.
This issue affects availability. It does not provide authentication bypass, privilege escalation, or direct password disclosure.
A user is vulnerable when all of the following are true:
1. The connection uses SCRAM-SHA-256 authentication. 2. The client reaches a malicious, compromised, or attacker-controlled PostgreSQL endpoint. 3. That endpoint sends a very large SCRAM PBKDF2 iteration count in the server-first-message.
In practice, that can happen in these situations:
- the application lets end users or tenants supply their own database connection details (as in many BI, reporting, analytics, ETL, and low-code platforms), so a user can point the shared client host at a server they control - the application accepts connection strings, hostnames, or JDBC URLs from user input, configuration uploaded by users, or other untrusted sources - the application is configured to connect to a PostgreSQL server that is itself malicious or later becomes compromised - the application connects through an untrusted proxy, relay, tunnel, bastion, or connection-pooling service that can act as the PostgreSQL server - an attacker can redirect the client to a fake PostgreSQL endpoint by manipulating DNS, service discovery, Kubernetes service resolution, /etc/hosts, environment variables, or similar indirection - an active network attacker on the path can impersonate the server because the connection does not strongly verify server identity (for example, sslmode lower than verify-full, or trusting a CA that signs hosts outside the operator's control)
The issue is more damaging when the application uses connection retries, many parallel connection attempts, or loginTimeout and assumes the timeout fully stops the work.
Patches The patch introduces a new connection property, scramMaxIterations, with a default of 100K. The client now rejects SCRAM server messages that advertise more PBKDF2 iterations than the configured cap before starting the PBKDF2 computation begins.
Workarounds
Until a patched version of pgjdbc is deployed, the following measures reduce exposure:
1. Only connect to trusted PostgreSQL servers whose identity is verified. Connect only to trusted PostgreSQL servers, and verify server identity with TLS using sslmode=verify-full and a trusted CA. TLS without certificate and hostname verification is not sufficient as an active network attacker can still impersonate the server.
2. Do not rely on loginTimeout as a complete mitigation on unpatched versions. On affected versions, loginTimeout can stop the waiting caller while the worker thread continues spending CPU.
3. Avoid SCRAM on untrusted or interceptable connection paths. For those paths, use an authentication method that does not let the server choose a SCRAM PBKDF2 iteration count.
4. Reduce blast radius operationally. Limit parallel connection attempts, add retry backoff, isolate connection establishment in a separate worker or process when possible, and apply CPU or container limits where appropriate.
5. On trusted servers you control, keep SCRAM iteration counts at ordinary values. This does not defend against an attacker-controlled server, but it avoids unnecessary client cost when talking to legitimate servers.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires cross-reference streams with repeated malformed cross-reference streams.
Patches
This has been fixed in pypdf==6.14.0.
Workarounds
If you cannot upgrade yet, consider applying the changes from PR #3887.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This requires parsing the content stream of a page with a not terminated inline image, as done when extracting the page text for example.
Patches
This has been fixed in pypdf==6.14.1.
Workarounds
If you cannot upgrade yet, consider applying the changes from PR #3891.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to large memory usage. This requires loading images where the declared size values are much too large compared to the actual data.
Patches
This has been fixed in pypdf==6.14.0.
Workarounds
If you cannot upgrade yet, consider applying the changes from PR #3888.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This requires parsing the content stream of a page with a not terminated inline image, as done when extracting the page text for example. It only affects the ASCII85 and ASCIIHex filters.
Patches
This has been fixed in pypdf==6.14.2.
Workarounds
If you cannot upgrade yet, consider applying the changes from PR #3892.
pypdf is a free and open-source pure-python PDF library. Prior to 6.13.3, a maliciously crafted PDF can cause DoS. An attacker who uses this vulnerability can craft a PDF which leads to large memory usage, as MAXDECLAREDSTREAMLENGTH is sometimes ignored. This requires parsing a content stream without a /Length value. This issue has been fixed in version 6.13.3.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This requires merging a file with threads/articles into a writer.
Patches
This has been fixed in pypdf==6.13.1.
Workarounds
If users cannot upgrade yet, consider applying the changes from PR #3839.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This requires merging a file with outlines into a writer.
Patches
This has been fixed in pypdf==6.13.0.
Workarounds
If you cannot upgrade yet, consider applying the changes from PR #3830.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This requires extracting the text in layout mode.
Patches
This has been fixed in pypdf==6.13.0.
Workarounds
If you cannot upgrade yet, consider applying the changes from PR #3830.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to large memory usage. This requires parsing large XMP metadata, possibly with lots of unnecessary elements.
Patches This has been fixed in pypdf==6.12.1.
Workarounds If you cannot upgrade yet, consider applying the changes from PR #3796.
Impact An attacker who uses this vulnerability can craft a PDF which leads to large memory usage. This requires extracting the text of a page which contains a form XObject with self-references.
Patches This has been fixed in pypdf==6.12.2.
Workarounds If you cannot upgrade yet, consider applying the changes from PR #3805.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires cross-reference streams with /W [0 0 0] values and large /Size values.
Patches
This has been fixed in pypdf==6.12.0.
Workarounds
If developers are unable to upgrade their apps immediately, they should consider applying the changes from PR #3791.
Impact An attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires accessing a stream which uses the /FlateDecode filter with a PNG predictor.
Patches This has been fixed in pypdf==6.12.2.
Workarounds If you cannot upgrade yet, consider applying the changes from PR #3806.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to large memory usage. This requires extracting text in layout mode with large character offsets.
Patches
This has been fixed in pypdf==6.12.0.
Workarounds
If developers are unable to immediately upgrade, they should consider applying the changes from PR #3790.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This requires accessing the children of a TreeObject, for example as part of outlines.
Patches
This has been fixed in pypdf==6.7.1.
Workarounds
If you cannot upgrade yet, consider applying the changes from PR #3645.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires a malformed /FlateDecode stream, where the byte-by-byte decompression is used.
Patches
This has been fixed in pypdf==6.7.1.
Workarounds
If you cannot upgrade yet, consider applying the changes from PR #3644.
Impact
An attacker who uses this vulnerability can craft a PDF which leads to long runtimes and large memory consumption. This requires parsing the /ToUnicode entry of a font with unusually large values, for example during text extraction.
Patches
This has been fixed in pypdf==6.7.1.
Workarounds
If you cannot upgrade yet, consider applying the changes from PR #3646.
OOM Denial of Service via Unbounded Array Allocation in Apache OpenNLP AbstractModelReader
Versions Affected:
before 1.9.5 before 2.5.9
before 3.0.0-M3
Description:
The AbstractModelReader methods getOutcomes(), getOutcomePatterns(), and getPredicates() each read a 32-bit signed integer count field from a binary model stream and pass that value directly to an array allocation (new String[numOutcomes], new int[numOCTypes][], new String[NUMPREDS]) without validating that the value is non-negative or within a reasonable bound. The count is therefore fully attacker-controlled when the model file originates from an untrusted source.
A crafted .bin model file in which any of these count fields is set to Integer.MAXVALUE (or any value large enough to exhaust the available heap) triggers an OutOfMemoryError at the array allocation itself, before the corresponding label or pattern data is consumed from the stream. The error occurs very early in deserialization: for a GIS model, getOutcomes() is reached after only the model-type string, the correction constant, and the correction parameter have been read; so the attacker pays no meaningful size cost to weaponize a payload, and a single small file can crash a JVM that loads it. Any code path that deserializes a .bin model is affected, including direct use of GenericModelReader and any higher-level component that delegates to it during model load.
The practical impact is denial of service against processes that load model files from untrusted or semi-trusted origins.
Mitigation:
2.x users should upgrade to 2.5.9.
3.x users should upgrade to 3.0.0-M3.
Note: The fix introduces an upper bound on each of the three count fields, checked before array allocation; counts that are negative or exceed the bound cause an IllegalArgumentException to be thrown and the read to fail fast with no large allocation. The default bound is 10,000,000, which is well above the entry counts of legitimate OpenNLP models but far below any value that would threaten heap exhaustion. Deployments that legitimately need to load models with more entries than the default can raise the limit at JVM startup by setting the OPENNLPMAXENTRIES system property to the desired positive integer (e.g. -DOPENNLPMAXENTRIES=50000000); invalid or non-positive values fall back to the default.
Users who cannot upgrade immediately should treat all .bin model files as untrusted input unless their provenance is verified, and should avoid loading models supplied by end users or fetched from third-party repositories without integrity checks.
Withdrawn Advisory This advisory has been withdrawn because evidence does not suggest that CVE-2022-42969 is a valid, reproducible vulnerability. This link is maintained to preserve external references.
Original Description The py library through 1.11.0 for Python allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data, because the InfoSvnCommand argument is mishandled.
The particular codepath in question is the regular expression at py.path.svnurl.InfoSvnCommand.lspattern and is only relevant when dealing with subversion (svn) projects. Notably the codepath is not used in the popular pytest project. The developers of the pytest package have released version 7.2.0 which removes their dependency on py. Users of pytest seeing alerts relating to this advisory may update to version 7.2.0 of pytest to resolve this issue. See https://github.com/pytest-dev/py/issues/287#issuecomment-1290407715 for additional context.
Easily exploitable vulnerability allows unauthenticated attacker with network access via multiple protocols to compromise Java SE. Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of Java SE.
An integer overflow in the ttvarloaditemvariationstore function of the Freetype library in versions 2.13.2 and 2.13.3 may allow for an out of bounds read operation when parsing HVAR/VVAR/MVAR tables in OpenType variable fonts. This issue is fixed in version 2.14.2.
3DES salt generation has a weakness when keys are repeated.
Difficult to exploit vulnerability allows unauthenticated attacker with network access via multiple protocols to compromise Java SE. Successful attacks require human interaction from a person other than the attacker. Successful attacks of this vulnerability can result in unauthorized access to critical data or complete access to all Java SE accessible data.
Difficult to exploit vulnerability allows unauthenticated attacker with network access via multiple protocols to compromise Java SE. Successful attacks of this vulnerability can result in unauthorized ability to cause a partial denial of service (partial DOS) of Java SE.
Last updated 2 June 2026
Easily exploitable vulnerability allows unauthenticated attacker with network access via multiple protocols to compromise Java SE. Successful attacks of this vulnerability can result in unauthorized access to critical data or complete access to all Java SE accessible data.
Apache Thrift: Java TSSLTransportFactory hostname verification
Difficult to exploit vulnerability allows unauthenticated attacker with logon to the infrastructure where Java SE executes to compromise Java SE. Successful attacks of this vulnerability can result in unauthorized read access to a subset of Java SE accessible data.
Certificate chain validation can result in stack overflow under certain circumstances.
Impact
The cookie name could be used to set other fields of the cookie, resulting in an unexpected cookie value. For example, serialize("userName=<script>alert('XSS3')</script>; Max-Age=2592000; a", value) would result in "userName=<script>alert('XSS3')</script>; Max-Age=2592000; a=test", setting userName cookie to <script> and ignoring value.
A similar escape can be used for path and domain, which could be abused to alter other fields of the cookie.
Patches
Upgrade to 0.7.0, which updates the validation for name, path, and domain.
Workarounds
Avoid passing untrusted or arbitrary values for these fields, ensure they are set by the application instead of user input.
References
https://github.com/jshttp/cookie/pull/167