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SECURITY.md
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@ -168,7 +168,7 @@ below).
Please use a descriptive subject line for your report email. After the initial
reply to your report, the security team will endeavor to keep you informed of
the progress being made towards a fix and announcement.
the progress being made towards a fix and announcement.
In addition, please include the following information along with your report:
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| Type | Versions affected | Reported by | Additional Information |
|--------------------|:-----------------:|-----------------------|-----------------------------|
| TensorFlow Lite TOCO FlatBuffer Parsing Vulnerability | <= 1.7 | Blade Team of Tencent | [security advisory](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/docs_src/security/advisory/tfsa-2018-003.md) |
| GIF File Parsing Null Pointer Dereference Error | <= 1.5 | Blade Team of Tencent | [security advisory](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/docs_src/security/advisory/tfsa-2018-002.md) |
| BMP File Parser Out-of-bounds Read | <= 1.6 | Blade Team of Tencent | [security advisory](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/docs_src/security/advisory/tfsa-2018-001.md) |
| Out Of Bounds Read | <=1.4 | Blade Team of Tencent | [issue report](https://github.com/tensorflow/tensorflow/issues/14959) |

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# Using TensorFlow Securely
Before using TensorFlow, please take a look at our security model, list of
recent security announcements, and ways you can report security issues to the
TensorFlow team at the
[https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md](Using
TensorFlow Securely) page on GitHub.

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## TFSA-2018-001: BMP File Parser Out-of-bounds Read.
### CVE Number
CVE-2018-7574
### Issue Description
The BMP (bitmap image file graphics format) decoder had an out-of-bounds read
due to insufficient checking of header sizes and signed integer values.
### Impact
The most likely consequence of this vulnerability would be that an invalid BMP
file could lead to an unhandled process crash, but may permit read access to
unintended regions of the TensorFlow process memory.
### Vulnerable Versions
TensorFlow 1.3.0, 1.3.1, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0
### Mitigation
We have patched the vulnerability in GitHub commits
[https://github.com/tensorflow/tensorflow/commit/49f73c55d56edffebde4bca4a407ad69c1cae4333c55](49f73c55).
If users are running TensorFlow in production or on untrusted data, they are
encouraged to apply this patch.
Additionally, this patch has already been integrated into TensorFlow 1.7.0 and
newer.
### Credits
This issue was discovered by the Blade Team of Tencent.

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## TFSA-2018-002: GIF File Parsing Null Pointer Dereference Error
### CVE Number
CVE-2018-7576
### Issue Description
When parsing certain invalid GIF files, an internal function in the GIF decoder
returned a null pointer, which was subsequently used as an argument to strcat.
### Impact
A maliciously crafted GIF could be used to cause the TensorFlow process to
crash.
### Vulnerable Versions
TensorFlow 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.3.1, 1 1.4.1, 1.5.0, 1.5.1
### Mitigation
We have patched the vulnerability in GitHub commit
[https://github.com/tensorflow/tensorflow/commit/c48431588e7cf8aff61d4c299231e3e925144df8](c4843158).
If users are running TensorFlow in production or on untrusted data, they are
encouraged to apply this patch.
Additionally, this patch has already been integrated into TensorFlow 1.6.0 and
newer.
### Credits
This issue was discovered by the Blade Team of Tencent.

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## TFSA-2018-003: TensorFlow Lite TOCO FlatBuffer Parsing Vulnerability
### CVE Number
CVE-2018-8825
### Issue Description
The TensorFlow Lite TOCO compiler does not perform correct boundary checks when
reading from some fields within TFLite files.
As background, TFLite files are based on the FlatBuffers serialization format,
which does not have bounds checking built-in, rather it relies on the clients to
handle the appropriate security checks by themselves.
In particular, TOCO is not performing correct bounds checks in the following places:
* Out of bounds read in TOCO in import.cc:42
* Null dereference in TOCO in import.cc:135
* Out of bounds read in TOCO in import.cc:104
* Null dereference in TOCO in import.cc:121
* Out of bounds read in TOCO in import.cc:62
* Out of bounds read in TOCO in operator.cc:48
* Out of bounds read in TOCO graph_transformations (propagate_fixed_sizes.cc:93)
### Impact
Users passing a malformed or malicious version of a TFLite graph into TOCO will
cause TOCO to crash or cause a buffer overflow, potentially allowing malicious
code to be executed.
### Vulnerable Versions
TensorFlow 1.5.0, 1.5.1, 1.6.0, 1.7.0
### Mitigation
We have patched the vulnerability in GitHub commits [https://github.com/tensorflow/tensorflow/commit/41335abb46f80ca644b5738550daef6136ba5476](41335abb) and
[https://github.com/tensorflow/tensorflow/commit/41335abb46f80ca644b5738550daef6136ba5476](41335abb) and
If users are running the TensorFlow TFLite TOCO compiler in production or on
untrusted data, they are encouraged to apply this patch.
Additionally, we have released TensorFlow version 1.7.1 to mitigate this
vulnerability.
### Credits
This issue was discovered by the Blade Team of Tencent.

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## TFSA-2018-004: Checkpoint Meta File Out-of-Bounds Read
### CVE Number
CVE-2018-7575
### Issue Description
The block size in meta file might contain a large int64 value which causes
an integer overflow upon addition. Subsequent code using n as index may cause
an out-of-bounds read.
### Impact
A maliciously crafted meta checkpoint could be used to cause the TensorFlow
process to perform an out of bounds read on in process memory.
### Vulnerable Versions
TensorFlow 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.3.1, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0
### Mitigation
We have patched the vulnerability in GitHub commit
[https://github.com/tensorflow/tensorflow/commit/d107fee1e4a9a4462f01564798d345802acc2aef](d107fee1).
If users are running TensorFlow on untrusted meta checkpoints, such as those
downloaded from the Internet, in production or on untrusted data, they are
encouraged to apply this patch.
Additionally, we have released TensorFlow version 1.7.1 to mitigate this
vulnerability.
### Credits
This issue was discovered by the Blade Team of Tencent.

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## TFSA-2018-005: Old Snappy Library Usage Resulting in Memcpy Parameter Overlap
### CVE Number
CVE-2018-7577
### Issue Description
TensorFlow checkpoint meta file uses Google's [https://github.com/google/snappy](snappy)
compression/decompression library. There is a memcpy-param-overlap issue in the
version of snappy currently used by TensorFlow.
### Impact
A maliciously crafted checkpoint meta file could cause TensorFlow to crash or
read from other parts of its process memory.
### Vulnerable Versions
TensorFlow 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.3.1, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0
### Mitigation
We have patched the vulnerability in GitHub commit
[https://github.com/tensorflow/tensorflow/commit/dfa9921e6343727b05f42f8d4a918b19528ff994](dfa9921e)
by upgrading the version of the snappy library used by TensorFlow to v1.1.7.
If users are loading untrusted checkpoints in TensorFlow, we encourage users to
apply the patch to upgrade snappy.
Additionally, we have released TensorFlow version 1.7.1 to mitigate this
vulnerability.
### Credits
This issue was discovered by the Blade Team of Tencent.

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## TFSA-2018-006: Crafted Configuration File results in Invalid Memory Access
### CVE Number
CVE-2018-10055
### Issue Description
A maliciously crafted configuration file passed into the TensorFlow XLA compiler
could cause an invalid memory access and/or a heap buffer overflow.
### Impact
A maliciously crafted configuration file could cause TensorFlow to crash or
read from other parts of its process memory.
### Vulnerable Versions
TensorFlow 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.3.1, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0
### Mitigation
We have patched the vulnerability in GitHub commit
[https://github.com/tensorflow/tensorflow/commit/c89ab82a82585cdaa90bf4911980e9e845909e78](c89ab82a).
If users are loading untrusted configurations in TensorFlow, we encourage users
to apply the patch to upgrade snappy or upgrade the version of TensorFlow they
are currently using.
Additionally, we have released TensorFlow version 1.7.1 to mitigate this
vulnerability.
### Credits
This issue was discovered by the Blade Team of Tencent.

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# TensorFlow Security Advisories
We regularly publish security advisories about using TensorFlow.
*Note*: In conjunction with these security advisories, we strongly encourage
TensorFlow users to read and understand TensorFlow's security model as outlined
in [https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md](SECURITY.md).
| Advisory Number | Type | Versions affected | Reported by | Additional Information |
|-----------------|--------------------|:-----------------:|-----------------------|-----------------------------|
| TFSA-2018-006 | Crafted Configuration File results in Invalid Memory Access | <= 1.7 | Blade Team of Tencent | |
| TFSA-2018-005 | Old Snappy Library Usage Resulting in Memcpy Parameter Overlap | <= 1.7 | Blade Team of Tencent | |
| TFSA-2018-004 | Checkpoint Meta File Out-of-Bounds Read | <= 1.7 | Blade Team of Tencent | |
| TFSA-2018-003 | TensorFlow Lite TOCO FlatBuffer Parsing Vulnerability | <= 1.7 | Blade Team of Tencent | |
| TFSA-2018-002 | GIF File Parsing Null Pointer Dereference Error | <= 1.5 | Blade Team of Tencent | |
| TFSA-2018-001 | BMP File Parser Out-of-bounds Read | <= 1.6 | Blade Team of Tencent | |
| - | Out Of Bounds Read | <=1.4 | Blade Team of Tencent | [issue report](https://github.com/tensorflow/tensorflow/issues/14959) |