Ramakrishnan Durairajan

72 papers A* 5A 7B 6C 2Misc 4Journal 17Unranked 31
YearRankTypeTitle / Venue / Authors
2026 conf
KDD (1)
Riya Ponraj, Ramakrishnan Durairajan, Yu Wang
2026 conf
NINeS
Chris Misa, Walter Willinger, Ramakrishnan Durairajan, Reza Rejaie
2025 conf
QuNet@SIGCOMM
Kevin Bohan, Bella Bose, Steven Corbato, Thinh Nguyen, Inder Monga, Brian Smith, Wenji Wu, Ramakrishnan Durairajan
2025 J jnl
IEEE Trans. Dependable Secur. Comput.
Matthew Nance Hall, Zaoxing Liu, Vyas Sekar, Ramakrishnan Durairajan
2025 conf
HotStorage
Long Tran, River Bartz, Ramakrishnan Durairajan, Ulrich Kremer, Sudarsun Kannan
2025 B conf
MASCOTS
Joseph Colton, Ramakrishnan Durairajan
2025 conf
CoNEXT (Short Papers)
Chris Misa, Walter Willinger, Ramakrishnan Durairajan, Reza Rejaie
2025 conf
MILCOM
Long Tran, River Bartz, Rajesh Sankaran, Ulrich Kremer, Ramakrishnan Durairajan, Sudarsun Kannan
2025 Misc conf
HotNets
Chris Misa, Ramakrishnan Durairajan
2025 J jnl
CoRR
Chris Misa, Ramakrishnan Durairajan
2025 conf
LEO-NET
Chris Misa, Ramakrishnan Durairajan
2025 J jnl
CoRR
Chris Misa, Ramakrishnan Durairajan, Arpit Gupta, Reza Rejaie, Walter Willinger
2025 A* conf
SIGCOMM
Caleb Wang, Ying Zhang, Qianli Dong, Esteban Carisimo, Ramakrishnan Durairajan, Fabián E. Bustamante
2025 A* conf
WWW
Miguel A. Bermejo-Agueda, Patricia Callejo, Rubén Cuevas, Ángel Cuevas, Ramakrishnan Durairajan, Reza Rejaie, Álvaro Mayol
2025 conf
NAIC
Chris Misa, Matthew Nance Hall, Reza Rejaie, Walter Willinger, Ramakrishnan Durairajan
2024 conf
PACMI@SOSP
Abduarraheem Elfandi, Hannah Sagalyn, Ramakrishnan Durairajan, Walter Willinger
2024 conf
PAM (2)
Aleksandr Stevens, Blaise Iradukunda, Brad Bailey, Ramakrishnan Durairajan
2024 J jnl
IEEE/ACM Trans. Netw.
Chris Misa, Ramakrishnan Durairajan, Reza Rejaie, Walter Willinger
2024 J jnl
IEEE Trans. Netw. Serv. Manag.
Matthew Nance Hall, Paul Barford, Klaus-Tycho Foerster, Ramakrishnan Durairajan
2024 A* conf
SP
Chris Misa, Ramakrishnan Durairajan, Arpit Gupta, Reza Rejaie, Walter Willinger
2024 conf
CloudNet
Joseph Colton, Ramakrishnan Durairajan, Reza Rejaie, Walter Willinger
2023 B conf
CLOUD
Bahador Yeganeh, Ramakrishnan Durairajan, Reza Rejaie, Walter Willinger
2023 conf
eBPF@SIGCOMM
Joel Sommers, Nolan Rudolph, Ramakrishnan Durairajan
2023 J jnl
SIGMETRICS Perform. Evaluation Rev.
Arpit Gupta, Ramakrishnan Durairajan, Walter Willinger
2023 conf
LEO-NET
Joseph Mclaughlin, Jee Choi, Ramakrishnan Durairajan
2022 J jnl
IEEE J. Sel. Areas Commun.
Jared Knofczynski, Ramakrishnan Durairajan, Walter Willinger
2022 Misc conf
NSDI
Chris Misa, Walt O'Connor, Ramakrishnan Durairajan, Reza Rejaie, Walter Willinger
2021 J jnl
Opt. Switch. Netw.
Matthew Nance Hall, Klaus-Tycho Foerster, Stefan Schmid, Ramakrishnan Durairajan
2021 conf
OptSys@SIGCOMM
Matthew Nance Hall, Paul Barford, Klaus-Tycho Foerster, Manya Ghobadi, William Jensen, Ramakrishnan Durairajan
2021 conf
TMA
Joel Sommers, Ramakrishnan Durairajan
2021 B conf
PAM
Juno Mayer, Valerie Sahakian, Emilie Hooft, Douglas Toomey, Ramakrishnan Durairajan
2021 J jnl
IEEE Netw.
Chris Misa, Ramakrishnan Durairajan, Reza Rejaie, Walter Willinger
2020 B conf
PAM
Bahador Yeganeh, Ramakrishnan Durairajan, Reza Rejaie, Walter Willinger
2020 conf
NetAI@SIGCOMM
Yukhe Lavinia, Ramakrishnan Durairajan, Reza Rejaie, Walter Willinger
2020 conf
TMA
Paul Barford, Ramakrishnan Durairajan, Matthew Nance Hall, Sathiya Kumaran Mani
2020 J jnl
CoRR
Matthew Nance Hall, Ramakrishnan Durairajan, Vyas Sekar
2020 conf
SPIN@SIGCOMM
Matthew Nance Hall, Guyue Liu, Ramakrishnan Durairajan, Vyas Sekar
2020 J jnl
Comput. Commun. Rev.
Chris Misa, Dennis Guse, Oliver Hohlfeld, Ramakrishnan Durairajan, Anna Sperotto, Alberto Dainotti, Reza Rejaie
2020 conf
HotStorage
Baber Khalid, Nolan Rudolph, Ramakrishnan Durairajan, Sudarsun Kannan
2020 conf
TMA
Soheil Jamshidi, Zayd Hammoudeh, Ramakrishnan Durairajan, Daniel Lowd, Reza Rejaie, Walter Willinger
2019 conf
LocalRec@SIGSPATIAL
Yugali Gullapalli, Jeremy Koritzinsky, Meenakshi Syamkumar, Paul Barford, Ramakrishnan Durairajan, Joel Sommers
2019 conf
ANRW
Chris Misa, Sudarsun Kannan, Ramakrishnan Durairajan
2019 C conf
ICMLA
Anirudh Muthukumar, Ramakrishnan Durairajan
2019 A conf
Internet Measurement Conference
Bahador Yeganeh, Ramakrishnan Durairajan, Reza Rejaie, Walter Willinger
2019 J jnl
Future Gener. Comput. Syst.
Roshan Lal Neupane, Travis Neely, Prasad Calyam, Nishant Chettri, Mark Vassell, Ramakrishnan Durairajan
2019 conf
ANRW
Sathiya Kumaran Mani, Paul Barford, Ramakrishnan Durairajan, Joel Sommers
2018 J jnl
CoRR
Sathiya Kumaran Mani, Ramakrishnan Durairajan, Paul Barford, Joel Sommers
2018 conf
IOT
Sathiya Kumaran Mani, Ramakrishnan Durairajan, Paul Barford, Joel Sommers
2018 A* conf
KDD
Giovanni Comarela, Ramakrishnan Durairajan, Paul Barford, Dino P. Christenson, Mark Crovella
2018 conf
MECOMM@SIGCOMM
Meenakshi Syamkumar, Paul Barford, Ramakrishnan Durairajan
2018 Misc conf
ICDCN
Roshan Lal Neupane, Travis Neely, Nishant Chettri, Mark Vassell, Yuanxun Zhang, Prasad Calyam, Ramakrishnan Durairajan
2018 J jnl
CoRR
Ramakrishnan Durairajan, Paul Barford, Joel Sommers, Walter Willinger
2018 A conf
Internet Measurement Conference
Robert Beverly, Ramakrishnan Durairajan, David Plonka, Justin P. Rohrer
2018 J jnl
CoRR
Robert Beverly, Ramakrishnan Durairajan, David Plonka, Justin P. Rohrer
2018 conf
ANRW
Ramakrishnan Durairajan, Carol Barford, Paul Barford
2018 conf
ITC (1)
Ramakrishnan Durairajan, Sathiya Kumaran Mani, Paul Barford, Robert D. Nowak, Joel Sommers
2018 J jnl
CoRR
Ramakrishnan Durairajan, Sathiya Kumaran Mani, Paul Barford, Robert D. Nowak, Joel Sommers
2018 B conf
Networking
Meenakshi Syamkumar, Sathiya Kumaran Mani, Ramakrishnan Durairajan, Paul Barford, Joel Sommers
2017 J jnl
Comput. Commun. Rev.
Ramakrishnan Durairajan, Paul Barford
2017 A conf
Internet Measurement Conference
Joel Sommers, Ramakrishnan Durairajan, Paul Barford
2016 conf
GAIA@SIGCOMM
Ramakrishnan Durairajan, Paul Barford
2016 C conf
VizSEC
Meenakshi Syamkumar, Ramakrishnan Durairajan, Paul Barford
2016 A conf
Internet Measurement Conference
Sathiya Kumaran Mani, Ramakrishnan Durairajan, Paul Barford, Joel Sommers
2015 A* conf
SIGCOMM
Ramakrishnan Durairajan, Paul Barford, Joel Sommers, Walter Willinger
2015 Misc conf
HotNets
Ramakrishnan Durairajan, Sathiya Kumaran Mani, Joel Sommers, Paul Barford
2015 conf
SPECTS@SummerSim
Mukta Gupta, Ramakrishnan Durairajan, Meenakshi Syamkumar, Paul Barford, Joel Sommers
2014 A conf
CoNEXT
Ramakrishnan Durairajan, Joel Sommers, Paul Barford
2014 A conf
Internet Measurement Conference
Ramakrishnan Durairajan, Joel Sommers, Paul Barford
2014 conf
HotSDN
Ramakrishnan Durairajan, Joel Sommers, Paul Barford
2013 B conf
IWQoS
Wenfei Wu, Yizheng Chen, Ramakrishnan Durairajan, Dongchan Kim, Ashok Anand, Aditya Akella
2013 conf
HotPlanet@SIGCOMM
Ramakrishnan Durairajan, Subhadip Ghosh, Xin Tang, Paul Barford, Brian Eriksson
2013 A conf
CoNEXT
Brian Eriksson, Ramakrishnan Durairajan, Paul Barford
redb/extractors/js_extractors/js_context.py
← Index redb/extractors/js_extractors/js_context.py python
"""Per-sample shared state for the JavaScript extractor pipeline.

A `JSContext` is built exactly once per JS sample (in `workers.py`) and threaded
into every extractor that runs against that sample. It owns the disk read, the
decoded source text, the line-split cache, the Shannon text-entropy figure, the
shared `scan_source()` results, and the pyjsparser AST. Each of those is
computed lazily through `cached_property` so an extractor that doesn't need a
particular artefact does not pay for it.

Without this object, every JS extractor instance redoes the same disk read,
decode, scan, and (for any consumer) AST parse. With it, every extractor
shares one set of results.

`JSExtractor.__init__` accepts the context via a `context=` kwarg; if absent
(e.g. unit tests instantiating an extractor directly with `source=...`) it
builds a fresh context from the constructor arguments. Either path produces a
fully-populated context, so extractor code can always rely on
`self._context.scan` / `self._context.ast` / etc.
"""

from __future__ import annotations

import math
from collections import Counter
from dataclasses import dataclass
from functools import cached_property
from typing import Any, Dict, List, Optional

import chardet

from redb.extractors.js_extractors.js_patterns import scan_source


def decode_source(raw_bytes: bytes) -> str:
    """Decode raw JS bytes to text, honouring BOMs and falling back to chardet.

    Mirrors the historical `JSExtractor._decode_source` logic so existing tests
    continue to round-trip identically.
    """
    if not raw_bytes:
        return ""

    if raw_bytes[:3] == b"\xef\xbb\xbf":
        return raw_bytes[3:].decode("utf-8", errors="replace")
    if raw_bytes[:2] in (b"\xff\xfe", b"\xfe\xff"):
        return raw_bytes.decode("utf-16", errors="replace")

    try:
        return raw_bytes.decode("utf-8")
    except UnicodeDecodeError:
        pass

    try:
        detected = chardet.detect(raw_bytes)
        if detected and detected.get("encoding"):
            return raw_bytes.decode(detected["encoding"], errors="replace")
    except Exception:
        pass

    return raw_bytes.decode("latin-1", errors="replace")


def _text_entropy(text: str) -> float:
    """Shannon entropy of the character distribution of `text`, rounded to 4dp."""
    if not text:
        return 0.0
    counter = Counter(text)
    length = len(text)
    entropy = 0.0
    for count in counter.values():
        p = count / length
        if p > 0:
            entropy -= p * math.log2(p)
    return round(entropy, 4)


@dataclass
class JSContext:
    """Shared raw materials for one JS sample, consumed by every JS extractor.

    Cheap attributes (raw_bytes, source) are populated eagerly by the factory.
    Expensive ones (scan, ast) are cached_property — computed on first access
    and reused across every extractor that holds the same context.

    `content_type` is the magika label (e.g. `"javascript"`) carried alongside
    the source so the new code_text_content writer (and any future generic
    text-content writer) can record it without re-running magika. Defaults to
    `"javascript"` because by construction this context type is JS-specific;
    workers.py supplies the actual magika value when it builds the context.
    """

    filepath: str
    raw_bytes: bytes
    source: str
    log: Any = None
    content_type: str = "javascript"
    # Populated by JSStringsExtractor.extract() (the decoded/reconstructed
    # strings — hex/unicode/charcode/base64/concat unpacked into plaintext).
    # Read post-loop by the IOC plumbing in workers.py so any IOCs hidden
    # behind those encodings get scraped from the decoded form. Stays None
    # if JSStringsExtractor didn't run for this sample.
    decoded_strings: Optional[list] = None

    @cached_property
    def lines(self) -> List[str]:
        return self.source.splitlines() if self.source else []

    @cached_property
    def text_entropy(self) -> float:
        return _text_entropy(self.source)

    @cached_property
    def scan(self) -> Dict[str, Dict[str, object]]:
        """Result of running scan_source() exactly once over self.source."""
        return scan_source(self.source) if self.source else {}

    @cached_property
    def ast(self) -> Optional[Any]:
        """Lazy pyjsparser AST. Returns None if the parser is missing or fails.

        Extractors should treat None AST as "fall back to regex" — every
        AST-consuming extractor already handles that path.
        """
        if not self.source:
            return None
        try:
            import pyjsparser
            return pyjsparser.parse(self.source)
        except ImportError:
            if self.log is not None:
                self.log.debug("pyjsparser not installed, AST analysis skipped")
        except Exception as e:
            if self.log is not None:
                self.log.warning(f"AST parsing failed for {self.filepath}: {e}")
        return None

    @cached_property
    def deobfuscated(self) -> "tuple[Optional[str], Optional[str]]":
        """Run the configured JS deobfuscator (with jsbeautifier fallback) once
        per sample and cache the result. Returns `(text, normalizer_used)` or
        `(None, None)` if neither path produced output.

        Computed lazily on first access — samples whose pipeline never reads
        this don't pay the subprocess cost.
        """
        from redb.extractors.js_extractors.js_deobfuscator import deobfuscate
        return deobfuscate(self.source, self.log)

    @cached_property
    def scan_deobfuscated(self) -> Dict[str, Dict[str, object]]:
        """Result of running scan_source() exactly once over the deobfuscated
        text, keyed by PATTERNS only (FEATURE_PATTERNS are not consulted by
        the dual-pass consumers). Empty dict when there is no deobfuscated
        text or it equals the raw source.

        Two extractors consume the post-deobf API surface:
        `JSSuspiciousAPIsExtractor` (for revealed_by_deobf rows) and
        `JSDeobfuscationExtractor` (for the new_apis_found diff). Caching here
        means we scan the deobfuscated text once instead of twice per sample.
        """
        from redb.extractors.js_extractors.js_patterns import PATTERNS
        deobf_text, _ = self.deobfuscated
        if not deobf_text or deobf_text == self.source:
            return {}
        return scan_source(deobf_text, patterns=(PATTERNS,))

    @cached_property
    def xray(self):
        """Run @nodesecure/js-x-ray once per sample and cache the result.

        Returns an `XRayResult` (always — the function collapses every failure
        path to an empty result so callers don't have to special-case missing
        Node, missing package, timeouts, or parse errors). The
        `JSFeaturesExtractor` reads it for the obfuscator family name and for
        corroborating warning kinds; the heuristic falls back cleanly when
        `xray.obfuscator is None`.
        """
        from redb.extractors.js_extractors.js_xray import run
        return run(self.source, self.log)

    @classmethod
    def from_path(
        cls,
        filepath: str,
        log: Any = None,
        source: Optional[str] = None,
        raw_bytes: Optional[bytes] = None,
        content_type: str = "javascript",
    ) -> "JSContext":
        """Build a context from disk. `raw_bytes` and `source` are optional
        overrides — useful when the caller has already read or decoded the file.
        `content_type` is the magika label workers.py dispatched on; it lands
        on the context for the code_text_content writer to record.
        """
        if raw_bytes is None:
            with open(filepath, "rb") as f:
                raw_bytes = f.read()
        if source is None:
            source = decode_source(raw_bytes)
        return cls(
            filepath=filepath,
            raw_bytes=raw_bytes,
            source=source,
            log=log,
            content_type=content_type,
        )