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 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==6.15.0.

Workarounds

If you cannot upgrade yet, consider applying the changes from PR #3944.

Impact An attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires a call to readuntilwhitespace with an input which does not have whitespace for a long time.

Patches This has been fixed in pypdf==6.15.0.

Workarounds If you cannot upgrade yet, consider applying the changes from PR #3947.

Impact

An attacker who uses this vulnerability can craft a PDF which leads to long runtimes and large memory consumption. This requires accessing the outlines of a document with either lots of entries or nested outlines with long re-used nesting paths.

Patches

This has been fixed in pypdf==6.16.1.

Workarounds

If you cannot upgrade yet, consider applying the changes from PR #3966.

Impact An attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This infinite loop blocks the current process and can utilize a single core of the CPU by 100%. It does not affect memory usage.

That is, for example, the case when the pypdf-user manipulates an incoming malicious PDF e.g. by merging it with another PDF or by adding annotations.

Patches The issue was fixed with #2264

Workarounds If you cannot update your version of pypdf, you should modify pypdf/generic/datastructures.py just like #2264 did.