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https://issues.apache.org/jira/browse/THRIFT-3175?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14567971#comment-14567971
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Dvir Volk commented on THRIFT-3175:
-----------------------------------
I can provide the simplistic patch we did, which is simply to define
MAX_LIST_SIZE to be 10,000 and check it. It fixed the issue for us (some race
condition on the client side sends garbled messages when 2 threads try to
serialize a message at once). If that's good enough - sure. Do you accept pull
requests via github or patches attached to tickets like in the pre-git days? I
haven't committed to thrift in ~4 years :)
> fastbinary.c python deserialize can cause huge allocations from garbage
> -----------------------------------------------------------------------
>
> Key: THRIFT-3175
> URL: https://issues.apache.org/jira/browse/THRIFT-3175
> Project: Thrift
> Issue Type: Bug
> Components: Python - Library
> Reporter: Dvir Volk
>
> In the fastbinary python deserializer, allocating a list is done like so:
> {code}
> len = readI32(input);
> if (!check_ssize_t_32(len)) {
> return NULL;
> }
> ret = PyList_New(len);
> {code}
> The only validation of len is that it's under INT_MAX. I've encountered a
> situation where upon receiving garbage input, and having len be read as
> something like 1 billion, the library treated this as a valid input,
> allocated gigs of RAM, and caused a server to crash.
> The quick fix I made was to limit list sizes to a sane value of a few
> thousands that more than suits my personal needs.
> But IMO this should be dealt with properly. One way that comes to mind is not
> pre-allocating the entire list in advance in case it's really big, and
> resizing it in smaller steps while reading the input.
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