From 05fb849470f8aed9c8571e1e58d0a7b4e4e4f630 Mon Sep 17 00:00:00 2001 From: Kartik Pattaswamy <62078498+kpattaswamy@users.noreply.github.com> Date: Thu, 2 Nov 2023 10:31:11 -0700 Subject: [PATCH] Update the protocol inference test infra with Mongo changes (#1758) Summary: Previously, the TShark command in the `dataset_generation` script was not able to decode Mongo pcap files and insert them to the dataset for evaluation. This PR adds a flag to the TShark command to decode traffic running through port 27017 as Mongo. The readme is also updated to provide information about the bidirectional connection level dataset. **Updates to the confusion matrix** In the previous image, the connections per protocol in the dataset seem to have been duplicated leading to a large number of connections per protocol. This may have been due to the `dataset_generation` script appending data to the `.tsv` files each time it was ran even though the underlying pcap file content/counts not being altered. Running the `dataset_generation` script with empty `.tsv` files with the same pcap files followed by the `eval` script resulted in a matrix showing much fewer number of connections per protocol, suggesting that there may have been duplication in the dataset previously. The connection counts for each protocol in the older dataset seem to have increased by a factor of 4x or 8x the count as the new dataset and makes sense as to why the inference accuracy remained constant between the old/new matrix. The TLS connection count had dropped in the new matrix by the previous number of Mongo connections (432) due to the new TShark command decoding mongo connections. The Mongo captures may have been previously captured in one of the early iterations of running the `dataset_generation` script and not updated since in the old dataset. **New mongo additions** In the old dataset, the Mongo pcap files were mainly of type `OP_QUERY` which is an opcode that Stirling does not currently process. More mongo pcap files of type `OP_MSG` were added to test the existing inference rule and this resulted in 0.9% being mislabeled as `unknown` due to request side data missing from the connection and the existing rule not supporting response side inference for `OP_MSG` packets. 0.7% was mislabeled as `pgsql` due to request side data also missing from the connection and the opcode of the packet being one which is not is not recognizable by Stirling. Related issues: https://github.com/pixie-io/pixie/issues/640 Type of change: /kind test-infra Test Plan: Ran the dataset generation and evaluation scripts with the new TShark flag and verified the `.tsv` files were created appropriately and the confusion matrix was as expected. Signed-off-by: Kartik Pattaswamy --- src/stirling/protocol_inference/README.md | 9 ++++++++- .../bi_directional_connection_matrix.png | Bin 232795 -> 164911 bytes .../protocol_inference/dataset_generation.py | 3 ++- 3 files changed, 10 insertions(+), 2 deletions(-) diff --git a/src/stirling/protocol_inference/README.md b/src/stirling/protocol_inference/README.md index 7aa4ec0a8d0..ea81ff8227c 100644 --- a/src/stirling/protocol_inference/README.md +++ b/src/stirling/protocol_inference/README.md @@ -62,9 +62,16 @@ which is defined uniquely by `src_addr`, `dst_addr`, `src_port`, and `dst_port`. a series of packets in a connection. The goal is to evaluate if a connection is eventually correctly classified over a period over time. +#### bidirectional-connection-level dataset + +One row in the bidirectional-connection-level dataset contains a series of packets over time in a bidrectional connection. +Packets on both directions of a connection are merged by their `src_addr`, `dst_addr`, `src_port`, and `dst_port` and grouped to +make the direction agnostic. This enables protocol inference on a series of packets in a bidirectional connection. The goal is +to evaluate if at least one side of a connection can be classified to infer the protocol of the entire bidirectional connection. + ## Protocol Inference Eval -There should be two tsv files `packet_dataset.tsv` and `conn_dataset.tsv` in the dataset folder. +There should be three tsv files `packet_dataset.tsv`, `conn_dataset.tsv` and `bi_dir_conn_dataset.tsv` in the dataset folder. Right now, available models are {ruleset_basic, ruleset_basic_conn}. ```shell script bazel run src/stirling/protocol_inference:eval -- --dataset --num_workers 8 diff --git a/src/stirling/protocol_inference/bi_directional_connection_matrix.png b/src/stirling/protocol_inference/bi_directional_connection_matrix.png index 2099f8de7d282229072b7d6414df7b422f28ccbc..4aef38d2e7570cbe5b99850a6d5a2ae6b6c8b3fe 100644 GIT binary patch literal 164911 zcmeFZcT|(jx;G5UBUVs(6crIHfJzkh;a-=&*{FjHo99>Y5&z1!EChu3YoFW@w=10Efxh--O?Al=Fq%;ogTw!&eP_ggJWIi~GXd z+&$HNH4pu0p$0y4FUubi|Ix(DRrAm_LlbdrxQC;-vYdjP!Xd5A;^N{O9yf2PnV!G+ zt2_9ndC1wz>yDbdypNBMoR5+m+`~!!gsQ5lyn>>+X5@=S_a! z=e(n*gNMrW>(Rb_?0@A`K?{bSdw zo{k>ca2OcVOY5)o`qlaGfBe-^L!SHSe@BX+bpCM_5L#=qhWy_aO>6U^m9+O@9rwGO zH@*Vi0mpIwcrSu~M}NM9&%CFcpYP=C=ixcSqkI1B6<^+|TKg zKYj94{E(i~TIIMxdt+3TMx%kEpX7L88-gZjtjL_NozbmSYCMv0C3S6%pLgS#cM0#- zZIMa7)f%5sP&u{_QMXMc+bPMfzFJ1{T(Zl$ey8s9$1no-C1S6ggB3SQW?WdA4S`%S 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z6FhV(BQ3238oAmN=FUHV!F$MJkfoua;nspeQZ1L>?NNodH?6I$xd$?K%IO|H^k8l? tW3B6ZY(Z7;fY%+%3xwYs&1CNHXp5ct8e5)5Sv%lA#mlOg0{NQ{|3Ano%OwB+ diff --git a/src/stirling/protocol_inference/dataset_generation.py b/src/stirling/protocol_inference/dataset_generation.py index abb7252575b..f5da3074fa3 100644 --- a/src/stirling/protocol_inference/dataset_generation.py +++ b/src/stirling/protocol_inference/dataset_generation.py @@ -86,7 +86,8 @@ def gen_tshark_cmd(): -e tcp.srcport \ -e udp.srcport \ -e tcp.dstport \ - -e udp.dstport" + -e udp.dstport \ + -d tcp.port==27017,mongo" for protocol, spec in ProtocolParsingSpecs.items(): field_name = spec["length_field"]